Thursday, February 02, 2006

Lean Advisory Tools (LAT) for Design and Operation of Job Shops

By Dr. Shahrukh A. Irani

PFAST (Production Flow Analysis and Simplification Toolkit) [For further details about PFAST, please visit] is a software tool that executes a suite of different algorithms and produces several outputs that together constitute a PFAST Analysis Report. Using one, or some combination, of the various outputs contained in the PFAST Analysis Report, a variety of strategies (Lean Advisory Tools, LAT’s), can be implemented to achieve Flow Production in any high-variety low-volume (HVLV) manufacturing facility. Starting with this issue of the JobshopLean journal, we will describe a series of LATs that can be implemented using PFAST and other COTS (Commercial Off The Shelf) software, if necessary.

LAT #1: Product Mix Segmentation using P-Q Analysis

Overview of the Strategy: Based on the annual production volume of each product, segment the product mix into Runners, Repeaters and Strangers ex. a low-variety high-volume (LVHV) segment and a high-variety low-volume (HVLV) segment. Next, break up and reorganize the existing facility into separate “mini-facilities” to separately produce each segment of the product mix. Each “mini-facility” will have an appropriate layout, equipment flexibility, material handling system, workforce flexibility and skill levels, inventory control policies, scheduling system, etc. suited for the particular segment of the product mix assigned to it.

Justification for this Strategy: Assembly lines, transfer lines and multi-product flow lines are best suited for the low-variety high-volume product mix segment. Whereas, multi-product cells, flexible manufacturing cells, hybrid cellular layouts and functional layouts are the preferred factory configuration for the high-variety low-volume product mix segment. The same production system cannot be optimal for these two distinctly different product mix segments. The main reason is the long vs. short production runs caused by the high vs. low production volumes, respectively, significantly impacts the number of setup changeovers, speed of operator learning and de-learning, stability of equipment/process parameters during operation, product mix diversity, and numerous other operating conditions that influence throughput, WIP and operating costs.

Implementation of this Strategy:
Muther’s method of P-Q Analysis can be used to segment the product mix based on the annual production volume of each product and then to determine the type of layout for any manufacturing facility – flowline, job shop, cellular (or some combination or a split of these three basic layouts) – best suited for each segment. The typical P-Q Analysis curve for an HVLV facility will show, at the left end of the curve, a relatively few products being produced in large quantities. These products are best produced on single- or multi-product production lines or in product-focused cells. Whereas, the right end of the same curve will show a great many different products being produced in small quantities that tend to be produced in a process (or departmental) layout, often referred to as a “job shop layout”. A “shallow” P-Q curve suggests a process layout for producing the entire product mix. Whereas, a “deep” curve suggests dividing the product mix into two or more segments and dedicating separate production areas, each with a different layout, to produce the different segments. For any job shop undertaking a Lean initiative, an essential starting point should be to understand the shape of their P-Q Analysis curve!

Illustrative Example from an Industry Project: Table 1 shows the input data for P-Q Analysis that must be provided to PFAST. PFAST uses only the “Part” and “Quantity” columns of data in this spreadsheet. Typically, the “Quantity” (# of pieces shipped) and “Revenue” ($ earned) for each part are for a year, or larger production horizon.
[A drawback of P-Q Analysis is that it does not factor in the Number of Orders that were placed for the part, and the time interval between each order. The average size of each order and the average inter-arrival time between repeat orders for the same part further helps to classify a product as a “Runner”, “Repeater” or “Stranger”. This enhancement of P-Q Analysis, P-Q-T Analysis (where T = Time), will be discussed in a future LAT.] The “Routing” is the sequence of work centers that a part must visit ex. Part No. 1 (80-A37353) has the routing: 17→6→2→11→10→29→54→55. Figure 1 and Table 2 are the graphical and tabular versions, respectively, of the P-Q Analysis output produced by PFAST. Question: Is this product mix only LVHV (low-variety high-volume), only HVLV (high-variety low volume) or some combination of the two extremes?

Sekine and Arai recommend checking if the P-Q Analysis curve is “shallow” or “deep” using 3 ratios as follows: Check the 2:8 ratio line i.e. the first 20% of the total number of products accounts for 80% of the Total (or Aggregate) Product Quantity. If that condition is not met, then check the 3:7 ratio line. If that condition is not met, then check the 4:6 ratio line. As the ratio increases in value from 0.25 to 0.67, that would indicate that the product mix is not dominated by a few high-volume “Runners”, and that the product mix contains “Repeaters” and “Strangers”. According to Sekine and Arai “… production lines that fall into the 4:6 ratio categories can be called wide-variety small-lot production lines. The typical Japanese factory falls into this category, but many are having problems succeeding at this kind of production”.

In Figure 1, the Parts are sequenced from left-to-right along the X-axis in order of decreasing value of Quantity of each (individual) part; whereas, the Y-axis on the left side of the graph shows the Quantity of each (individual) part and the Y-axis on the right side of the graph shows the Aggregate Quantity for any group of parts picked based on the three ratios recommended by Sekine and Arai. In this particular example, the curve is “deep” and Figure 1 shows a potential segmentation of the product mix into High-Volume (Runners), Medium-Volume (Repeaters) and Low-Volume (Strangers) segments.

In Table 1, where the parts have been sorted in order of decreasing value of Quantity, the three ratio lines are shown for 60%, 69% and 80% of the Total Aggregate Quantity (which is 1766478, as shown in Row # 79 of the table). With reference to the table, 13 parts (which is 16% of the entire product mix of 79 parts) account for 60% of the Total Aggregate Quantity, 17 parts (which is 21% of the entire product mix of 79 parts) account for 69% of the Total Aggregate Quantity and 29 parts (which is 29% of the entire product mix of 79 parts) account for 80% of the Total Aggregate Quantity.

So, using Figure 1 and Table 2 to answer the question that was posed earlier in this section – Is this product mix only LVHV (low-variety high-volume), only HVLV (high-variety low volume) or some combination of the two extremes – I chose to break up the product mix of this forge shop into at least two segments, one comprised of the top 23 parts and the other containing the remaining parts. What do you think?

Planning Improvement Projects based on these Results: How does one translate the results obtained using this LAT into improvement projects (or kaizen events) that reduce/eliminate the Seven Types of Waste, increase throughput at capacity constraints, reduce inventory levels and reduce operating costs? Here are some examples of the follow-on projects that could be undertaken after this product mix segmentation analysis is completed –
  • The typical product mix in an HVLV facility tends to be large. Therefore, collecting the relevant data for all products would be difficult and costly. Say that management desires to conduct one or more kaizen events that focus on reduction of material handling costs, standardization of storage containers, and improvement of shop floor communications. This would require data collection to generate Value Stream Maps, Flow Process Charts and Material Handling Planning Charts, as part of a larger Systematic Handling Analysis (SHA) initiative. Using P-Q Analysis, one could quickly select one (or more) products from the High-Volume segment, and ignore the Low-Volume products for the time-being.
  • For any pair of work centers in any manufacturing facility, a key driver of Material Handling Cost is the total time that material handlers spend moving material between those two locations. This time is a function of travel distance between the locations and the number of trips made between them. The number of trips is directly proportional to the total volume of different products in whose routings these two work centers appear consecutively. So, if it is desired to lower the total Material Handling Cost for a facility, P-Q Analysis would immediately point those work centers that feature in the routings of the products in the High-Volume segment.
  • Both segments of the product mix – low-variety high-volume and high-variety low-volume – could be analyzed for the existence of products with identical or very similar routings. For each product family identified in the High-Volume segment, a multi-product flowline could be designed. For each product family identified in the Medium-Volume segment, a flexible multi-product cell could be designed since any individual product may not have the demand to justify a dedicated cell. But, for the product families identified in the Low-Volume segment, I would do things differently as follows: (i) a flexible cell could be designed for each family and (ii) the remaining parts i.e. those that do not belong in any family in this segment, I would strongly recommend “culling” them from the product mix. Unless, of course, those parts are being supplied to the very customers whose parts also belong in the High-Volume segment! In which case, setup reduction and flexible manufacturing equipment could become priorities for the kaizen events. In fact, I personally know the Plant Manager at a local sheet metal fabrication job shop who referred to this product mix rationalization that they did as “sending our difficult and costly parts to our competitors”!


    Burbidge, John L. (1996). Production Flow Analysis for Planning Group Technology. New York, NY: Oxford University Press. ISBN 19-856459-7.

    Irani, S. A. & Huang, H. (2005) Hybrid Cellular Layouts: New Ideas for Design of Flexible and Lean Layouts for Jobshops. Columbus, OH: Zip Publishing (

    Sekine, K. & Arai, K. (1992). Kaizen for Quick Changeover: Going beyond SMED. Cambridge, MA: Productivity Press. ISBN 0-915299-38-0.

    Dr. Shahrukh A. Irani is an Associate Professor in the Department of Industrial, Welding and Systems Engineering at The Ohio State University, Columbus, OH. He can be reached at or (614) 688-4685.

Just My Two $en$e

By Dr. Shahrukh A. Irani

The goal of this column is to provide quick and simple advice to the job shop owner who seeks to implement best practices. For example, during a recent tour of a fabrication job shop to assess their efforts to implement Lean, the President/Owner repeatedly said that he was finding it difficult to get his employees to embrace Lean Thinking as part of their day-to-day work. For any buzzword like Lean or Six Sigma or Quick Response Manufacturing to “stick” in a small organization, the employees have to see and be convinced that their boss and top execs are “with the program”. How could the President/Owner of this small shop, who by the way is a friend of mine, lead his people by personal example to whole-heartedly adopt Lean Thinking? Here are my views on some basic qualities of leadership that this owner must have (or develop) and demonstrate.The 4H’s of a Good LeaderThere are the 3P’s (Production Preparation Process), then the 5M’s (Man, Machines, Methods, Materials and Measures) for problem-solving using Ishikawa Diagrams, and, of course, the 6S’s (Sort, Shine, Set, Standardize, Sustain and Safety) of visual workplace design. Well, how about the 4H’s of being a good leader? Head, Heart, Hands and Hoofs. Yes, I mean Hoofs! Now you could get really mad at me that I would call you, who are a successful and respected owner of a small shop, a horse or a moose? You would have preferred FEET. Right? But then it would no longer have been sexy to propose the 3H1F instead of the 4H’s. Nope! The hoofs are for you to walk your facility to see waste, to note opportunities for improvements, to get a pulse of who is goofing off versus who is doing a stellar job, and more. So here are the 4H’s of good leadership that I described over lunch to this job shop owner friend of mine:


  • Be creative in seeking avenues to increase cash flow
  • Keep abreast of latest developments and ensure that you yourself are very knowledgeable about Lean
  • Do not expect a consultant or employee to do the thinking for you!
  • Understand your business and bid on work that fits within your core competencies
  • Spend extra time to do a Risk vs. Benefit analysis when you choose to enter into new markets and bid on complex jobs that you have not run even once before
  • Hire new employees who are aware of the latest developments in your industry


  • Be 100% sure that Lean is going to work for you
  • Be passionate about making your business succeed
  • Treat your employees like family and make them feel that their success is your success
  • Have the courage to accept that an employee may know better than you
  • Have the courage to get rid of old-timers who are proving to be anchor-draggers and retain younger employees who may have the right attitude to embrace Lean


  • Wave to your employees as you walk through the facility daily
  • Shake the hands of those whose work shines
  • Reach into your wallet to pull out money for training and investment in your employees and facility improvements
  • Embrace your employees (Have you observed Dick Vermeil, the coach of the Kansas City Chiefs, as he interacts with his team on the sidelines during any NFL game?)
  • Participate actively in improvement events so you can show by example how to do things
  • Demonstrate your own competence, be a teacher and tutor and mentor, and not a boss for once!
  • Give the heave-ho to old-timers who are proving to be anchor-draggers


  • Walk your facility, and when you see examples of waste, note them, maybe take a photo; then, return to your office and create a PowerPoint slideshow, indicate various opportunities for improvements in each photo, and attach a $ value to each (Tell your employees exactly how you would like them also to see and value waste!)
  • Look around your shop and get a pulse of who is goofing off versus who is doing a stellar job
  • Go and post results on the notice board that acknowledge specific employees for how much their suggestions saved you (or earned you more in terms of additional business that you attracted)
  • Drive out to your customers and tour their facilities so you can benchmark
  • Drive out to your suppliers and tour their facilities, maybe try to teach them Lean so they "get with the game" and complement your own internal projects

That is it! If you would like to add to the 4H's of leadership that are essential to implement Lean in small, resource-constrained companies, go right ahead and respond to this column. And, if you wish to write this column for the next issue of the JobshopLean journal, please let me know.

Dr. Shahrukh A. Irani is an Associate Professor in the Department of Industrial, Welding and Systems Engineering at The Ohio State University, Columbus, OH. He can be reached at or (614) 688-4685.

Tuesday, January 03, 2006

JobshopLean: A Journal for Best Practices suited to High-Variety Low-Volume Small- and Medium-sized Manufacturers

By Dr. Shahrukh Irani:

It was sometime in 2000 that a colleague of mine teaching a course on Product Design recommended that I read Lean Thinking by James Womack and Daniel Jones. That was when it hit me like a ton of bricks that Toyota teaches and practices Industrial Engineering (IE) the way it has never been taught, researched and practiced in the US. I revamped my teaching philosophy and research program to completely focus on re-learning and advancing the practice of the science of IE.

I had to learn about the Toyota Production System (TPS) in a hurry. The Web proved to be an invaluable resource, especially the NWLEAN online chat group founded by Bill Kluk, the Superfactory website created by Kevin Meyer and the discussion forums of the Lean Enterprise Institute founded by Jim Womack. Just about everybody but myself had been learning and implementing TPS best practices for years!

But, with hundreds of experts on TPS already out there saying and doing the same things, there was neither much opportunity nor any challenge in following the beaten track. If someone was fortunate enough to have been trained by one or other Toyota sensei, then that appeared to put them head and shoulders above anybody else. I wondered why because so much of TPS is rehashed IE. Was no IE in the US capable of improving the TPS best practices developed in the pre-computer era of the early 1960’s? Yes, that one “counter-thinker” was Professor Rajan Suri, Director of the Center for Quick Response Manufacturing (QRM) at the University of Wisconsin-Madison. I admired and respected his ideas and methods, especially since his research resulted in the commercial MPX Rapid Modeling software. Still, I found that when QRM was applied in the high-variety low-volume environments of captive and independent jobshops
[1], it came up short in many ways[2]. For the MTO (Make-To-Order) business environment of the typical jobshop, a Cellular Layout may not be flexible, agile, reconfigurable and adaptive to the dynamics and uncertainties of the environment.

I realized that my project-intensive courses and research had given me considerable exposure to the operational conditions, needs and opportunities of small manufacturers. So, I thought to myself, “TPS was developed primarily for assembly line-type manufacturers. Why not start at the opposite end of an OEM’s supply chain? Why not create an online group like NWLEAN that deals exclusively with the needs of jobshops and other custom manufacturers?” So, in August 2001, I started the JSLean (JobshopLean) online chat group that today has about 1100 members. Every new member joining the group receives the following email welcoming them to the group:

Welcome to Jobshop Lean (JSLEAN), an online resource center and discussion group to serve high-variety low-volume (HVLV) manufacturers. Examples of HVLV manufacturers would be small and medium-sized enterprises (SME’s) that are jobshops (machining, welding fabrication, stamping, die-casting, forging, injection molding, contract electronic assembly, etc.), re-manufacturers, repair and maintenance facilities, Make-To-Order and Engineer-To-Order manufacturers of customized assemblies (furniture, security cabinets, cranes, tractors) and feeder shops located in vertically integrated factories (munitions, ships, industrial equipment and jet engines). Inspired by the successes of automotive and aerospace assembly factories and their Tier 1 and Tier 2 suppliers that have adopted or adapted the famous Toyota Production System (TPS), many other manufacturers have sought to implement Lean Manufacturing in their facilities. However, it is important to distinguish between “Assembly Line Lean” and “Jobshop (or HVLV) Lean”.

As the moderator of the JSLean chat group I created considerable controversy by repeatedly and vociferously arguing that TPS just does not relate sufficiently to the needs of high-variety low-volume (HVLV) manufacturers. Fortunately, there were a few members (Mark Warren, Robert Tristani, Shardul Phadnis, Sid Schaaf, Michael Mahoney, Prasad Velaga, to mention a few) who understood the limitations of TPS and actively discussed best practices that are best suited to HVLV environments. One member – Mark Warren – not only has decades of industry experience but he also has a strong scholarly bent, which led him to research the history of TPS and write white papers, books and articles that he posted on his website. Every time he posted to the group, he would further convince me that I wanted to work with him to establish JobshopLean as the “other Lean” that Toyota has not mastered!

Next, I got a subscription to Target magazine published by the AME (Association for Manufacturing Excellence). It is a superb magazine published by a great professional organization that carries far more useful articles for an IE in manufacturing than does Industrial Engineer, the flagship trade journal of the IE profession! Then, I got a subscription to the monthly newsletter, Lean Manufacturing Advisor, published by Productivity Press. Every issue of this newsletter impressed me because it showed the extent to which the ideas and methods and tools of TPS could revolutionize how IE is practiced in the US. But, in both magazines, the articles on Lean for jobshops were superficial and cookie cutter-like in methodology, never extending beyond the obvious low-hanging fruits. Worst of all, there was nothing by way of computer-aided methodology and software to address the unique and complex problems of small and medium-sized enterprises (SMEs) who are simply not like Toyota! I could not help but wonder, “How can US manufacturers ever hope to beat their offshore competitors by following and copying the very approaches that are being used to beat them?”

After nearly five years as the moderator of the JSLean chat group, with blogs promoting the same old Lean Thinking that lacks innovation and is phobic towards IT-enabled best practices, I decided to start a journal that featured columns by the best and brightest practitioners of JobshopLean. So I talked to Mark Warren and several other active members of the JSLean chat group if they would like to write for this electronic journal. I am happy to report that they all did!

So here is the inaugural issue of the JobshopLean electronic journal. Our inspiration and challenge is to go beyond the Toyota Production System and develop new flexible, agile, adaptive and reconfigurable production systems suited for the 21st Century. Our goal is to develop and share ideas, methods, tools, experiences, etc. that are specific to high-variety low-volume small- and medium-sized manufacturers (SMM’s) anywhere in the world.

[1] A captive jobshop makes a large variety of components required to assemble a product (or product family) being produced by a specific OEM ex. a turbine manufacturer for whom we did a project asked us to reorganize their Small Parts Machine Shop that had a parts list of about 3300 components. An independent jobshop also makes a large variety of components but for a diverse customer base that could include several OEMs.
[2] Despite having devoted my early career to Cellular Manufacturing, I no longer feel that manufacturing cells are the best facility configuration for a typical jobshop, at least not in the IT-era where concepts like virtual cells are realizable.

Dr. Shahrukh A. Irani is an Associate Professor in the Department of Industrial, Welding and Systems Engineering at The Ohio State University, Columbus, OH. He can be reached at or (614) 688-4685.

Monday, January 02, 2006

Challenges of Implementing Lean in a Job Shop

By Dr. Shahrukh A. Irani:

The number of books that describe the standard (and mature) best practices of the Toyota Production System (TPS) could fill an entire room. But, I can count on the fingertips of one hand the how-to books for customizing Lean Thinking for the design and operation of profitable job shops. The number of OEM’s is small, but the number of job shop-type manufacturers in the US is in the 100,000’s. A job shop operates in dynamic and uncertain conditions and is faced by challenges that are completely opposite to those of the TPS, such as (i) customers could be here today but gone tomorrow? (ii) demand forecasts are unreliable or non-existent? (iii) suppliers may not be prepared to deliver JIT? (iv) equipment must be multi-function, and not right-sized, to compensate for a small workforce? (v) drawings, route sheets, inspection plans, gauges, tools, work instructions, etc. need to be developed from scratch to even bid on new orders? Etc.

Since 1996, by virtue of my teaching and research thrusts here at The Ohio State University, I have been able to observe, document and analyze (and sometimes even solve) problems that I know to be clearly unique to job shops and other HVLV manufacturers. Here is a sample of the “grand” challenges that I have identified that could never be solved by a TPS guru:

  • How does a job shop owner, who may not understand Lean or have worked previously at a company that practiced Lean, suddenly become the driving force behind a radically new operating strategy?
  • How does a job shop develop a multi-skilled and knowledgeable workforce with the self-motivation to proactively seek and eliminate the Eight Types of Waste in administrative and production processes?
  • How should a job shop segment and manage a product mix which contains anywhere from 500 to 5000+ routings?
  • How should a job shop design its facility layout when only a small proportion of its product mix can be produced in dedicated cells? (There is no single facility layout that is suited for Flow Production, is flexible and reconfigurable to adapt to changes in product mix, demand volumes and manufacturing technology.)
  • How does a job shop define and distill its “core competencies” into a guidebook of rules and decision-making flowcharts to rapidly and reliably and effectively accept, evaluate or reject new orders?
  • How does a job shop implement Finite Capacity Scheduling without purchasing expensive software, and employing a full-time staff person?
  • How does a job shop train their material handlers to also perform scheduling, order progressing and shop floor control tasks whereby they serve as Value Stream Managers for virtual cells producing families of parts?
  • How does a job shop adopt real-time inventory tracking technology utilized in warehouses and distribution centers without purchasing expensive software, and employing a full-time staff person?

The above list of challenges is far from complete. But these are some of the knotty problems that JobshopLean seeks to solve! I personally believe that the time has arrived for the small- and medium-sized manufacturers in the US to develop a novel production system, one that is inspired by but far from being a bad copy of the Toyota Production System. Decades ago, after the Second World War, the Training Within Industry (TWI) program became a stepping stone for Toyota to becoming the automobile giant that they are today. Let us strive to once again lead the rest of the world by developing the ideas, methods and tools for deploying Lean + Flexibility + Agility + Reconfigurability in small-to-medium sized high-variety low-volume manufacturing facilities!

Dr. Shahrukh A. Irani is an Associate Professor in the Department of Industrial, Welding and Systems Engineering at The Ohio State University, Columbus, OH. He can be reached at or (614) 688-4685.

Sunday, January 01, 2006

An Assembly Plant is not a Job Shop

By Dr. Shahrukh A. Irani:

The Toyota Production System (TPS) was designed for assembly of automobiles. Sure, an assembly line can flex to make a range of models and allow customization of individual cars to suit particular customers. But, every car is still a car. The same cannot be said about a job shop that is making shafts, gears, wheel hubs and disc drive components under the same roof. So how does a low-variety high-volume (LVHV) assembly line differ from a high-variety low-volume (HVLV) job shop? Here are some specific differences between the two manufacturing systems:

Product Variety: An assembly line is designed for a product family, or products that share common platforms and assembly configurations. In contrast, the product mix of a job shop contains a large number of dissimilar routings. By no means is this a trivial problem that can be solved using a spreadsheet (or database) software! Also, the product mix of a job shop tends to change during each year, as customers revise their supplier base and outsourcing strategies.

Layout: An assembly line has a conveyor-paced flow pattern with a well-defined linear or branched structure that is dictated by the assembly process for a specific product, or product family. In contrast, the typical job shop usually has a process layout with similar machines being grouped into departments (or “process villages”). This is a common mistake and downfall of a job shop! Neither is a cellular layout a panacea since it reduces the flexibility and agility to respond to changes in product mix and demand volumes. Frankly, no single layout (process, cellular, flowline) fits a job shop; usually, a hybrid combination of these traditional layouts is the best option!

Demand Volumes: An assembly line tends to produce a few products in high volumes, primarily because an OEM has the power to dictate product mix and supply quantities to customers. In contrast, a job shop may have low demand volumes and volatile demand patterns since their customers tend to change their orders (mix, volume, due dates, delivery frequency and lot sizes, etc.) frequently, often at short notice.

Product Design and Process Engineering: An assembly line benefits from “variant design” because every new model for a car does not change completely from the previous year’s model. In contrast, a job shop often needs to design and manufacture parts and products that have little, or no, similarity to past orders. In fact, every job shop ought to evaluate their product mix to identify product families, organize their design and manufacturing data on a family-by-family basis and store this knowledge in an electronic design retrieval and process planning system.

Production Scheduling: An assembly line is scheduled using Takt Time, Heijunka (Production Smoothing) and Pull based on Kanban signals. There exists a unique class of algorithms for design and balancing of single (or mixed model) assembly lines. In contrast, the multi-product multi-machine Job shop Scheduling problem is characterized by jobs with due dates, sequence-dependent setup changeover times, high variability among job parameters (setup times, cycle times, lot sizes, routings, etc.)! The class of algorithms to solve the Job shop Scheduling problem is completely different from those used for assembly line scheduling. The very idea of Pull Scheduling assumes a linear flow production system and repeatability of demand for a product (or product family). A job shop owner would be fortunate to enjoy these luxuries in his/her business environment!

Availability of Internal Resources: Any OEM like Toyota or Boeing or Ford has the resources to hire full-time engineers or consulting companies to teach and train their staff, even help with implementing TPS best practices in their assembly facilities. In contrast, a job shop often lacks full-time personnel, technical resources and finances required to develop, teach and sustain a comprehensive in-house program for Lean Six Sigma.

This list of differences between the two manufacturing systems – Assembly Line and Job shop – is much longer! It is not my intention to take anything away from what the architects of the TPS have achieved. However, it must be recognized that the typical high-variety low-volume (HVLV) manufacturer operates in a Make-To-Order business environment. An extensive suite of well-documented and easy methods and tools to implement Lean in a job shop simply does not exist. The JobshopLean journal will provide the thousands of job shop-type manufacturers in the US with ideas, best practices and tools developed specifically for their business and operating environments!

Dr. Shahrukh A. Irani is an Associate Professor in the Department of Industrial, Welding and Systems Engineering at The Ohio State University, Columbus, OH. He can be reached at or (614) 688-4685.

Pressure on Prices: How will you Respond?

By Dr. Anil Menawat:

Increased telecommunications technologies are making it easier for customers to shop globally for lower prices. While customers everywhere are enjoying more options and lower prices, here in North America, raw material and energy costs are rising, creating unprecedented challenges for manufacturers. Only a select few are able to pass the increased cost to their customers while most are sacrificing profits to stay in the game. How will you respond to this power shift?
Before we begin I would like to say that I am honored as well as delighted on the invitation to be a part of this eJournal. The suggestion of exploring ideas that go beyond the applicability of the “Toyota Production System” is refreshing. In my opinion, this is a very important topic in multi-product and variable-demand environment often found in the SMB (small and medium-sized business) sector.

Where is the Opportunity?

When manufacturers are unable to pass the increased cost to their customers, they usually adopt one or both of the following strategies:
(1) To reduce the internal costs of producing products and services, and
(2) To discontinue the unprofitable products, services, channels or customers.
In either case, they first need an accurate measurement of costs to determine true profit margins for each product and service. Without a true assessment of the costs it is difficult to identify where the opportunities lie and what can be done about them. Furthermore the interest is less in what their costs were in the past and more in what they will be in the future for them to stay competitive.
Most companies focus on tracking past performances and then tend to extrapolate from that to forecast future operational requirements and capabilities. Unfortunately, your past performance, no matter how successful, was based on different work requirements, demands, customer needs, and market conditions. Operating approaches and strategies that may have helped you in the past may not produce the desired result in the future because the environment has changed. In multi-product environments where demand fluctuates routinely, such as in high-variety and low-volume scenarios, this is an everyday event.
Measuring revenues is not a problem but getting true cost of each product and service is. Most companies keep good accounting data and the problem is not in adding up the cost. The problem is in distributing them to each product and service. If your product mix, demand volumes, and how you produce your products or services do not change significantly then you can use standard costing with variance analysis to get a fairly good assessment. But, that is not the environment in which the typical SMB operates. The high variety of products and fluctuating demands make the standard cost data misleading. The per-piece cost for each unit of product depends on the dynamics of the operating environment on the shop floor at the time that piece was produced. The product mix and the demand volumes impact the activities required to meet the demand. The activities composition plays the most important role in how to absorb the costs – in particular the costs of technology, capital investment, back office, design, maintenance, holding inventory, etc.
Today your operational environment is different from when the standard cost structure was developed. Today the product mix is different, the demand volumes are different, and in many cases, the policies and procedures are also different. A considerable constitution of the activities by people and machines required to deliver the products or services is new. Most companies in the SMB sector do not have the resources to update their cost structures frequently hence we find them to be out of date in great majority of situations. In some cases we have seen standard cost information to be more than several decades old. Clearly the company made a different set of products back then, than it does today.
For the sake of discussion let us assume that we can overcome all these inadequacies, but the main problem still remains that this is historical information and not forward looking into the future. In your quest to respond to the price pressures when you make any significant change in your operating dynamics, you will be operating in a new and different environment. Your decisions on what to do must be made with the cost structures based on the yet unknown future. If they are based on the past cost structures then you are more than likely to go off course.

Uncertainty engenders partial solutions and misapplications

When faced with the rising pressure on prices, we find that managers often jump to conclusions – improve process efficiency, improve throughput, reduce inventory, reduce labor cost, outsource to a cheaper producer, etc. These are good things to do per se, so long as you are taking the cost out of the system and not merely shifting it to another area. In majority cases we find shifting costs to be the more common response. But, more importantly, the elimination in cost must be significant enough to make an impact. Very often managers forget to ask the four basic questions:
  • Can it be done? Is it possible? If not, then what additional capabilities are needed?
  • Will it be profitable?
  • What is the impact of my decision across the product mix and the functional capabilities of the organization?
  • How do I get to my desired future (the roadmap)?

In the absence of answers to these questions, the environment is fertile for half-baked ideas based on correlative thinking and rules-of-thumb, and misapplications of sound principles. Let us consider the implications of this uncertainty. The results are far reaching that affect not only the accountants and senior managers, but also the operations personnel. Process managers are asked to redesign the process and policies that will reduce costs and increase profits in future based on historical information. Without a reliable framework they do not know for sure whether their solutions will bear any fruit. They are left to use vague guidelines, which depend on inaccurate information, without questioning the accuracy and accepting on faith. They shoot in the dark and hope to kill. Misapplications are rampant throughout industry.

An example of misapplication and shifting costs

Let’s consider an example of a truck power-train component supplier. The company manufactured twenty four product families with several hundred individual SKUs. The demand of various products varied from a paltry 2 units for some to several thousand for others over a four-week long period. The plant operated in a batch fashion with two primary routings but no direct connecting flow between workstations. In other words, each work station continued to produce until it ran out of work to do. The plant financials were good with overall net income at almost 7% of sales. Unfortunately, WIP piled up everywhere. Management decided to convert the batch operation into a flow line to improve efficiency and reduce WIP.
Using an aggregated constraint capacity analysis tool they were convinced that their plan was feasible. They sized the buffers based on historical performance and line balancing showed a lot of promise. They estimated the WIP to decline precipitously with overall increase in bottleneck efficiency. Using the standard costing model, adjusted for the expected improvement in efficiency, they believed they were going to save a lot of money.
The reality unfortunately was not as they expected. Reduced WIP choked the flow and the machine utilization rates suffered significantly reducing the overall throughput by about 20%. The financial result was a disaster; the overall net income fell to negative 3% of sales. They not only lost on the bottom line but they also lost on the top line since they could not produce enough to meet the customer demand and had to outsource to fill the gap.
The problem was not in their objectives but in their analytical tools and the applicability of the principles. They were attempting to squeeze a square peg in a round hole. The problems emanated from two causes:
1. The processing requirements at workstations depended on individual product type, and
2. They did not understand how the machine failures would impact the dynamic interactions throughout the process.
If the processing requirements at workstations in a line depend on each product then with each change in product batch the dynamics of the entire line changes. Not having large enough buffers (WIP) in between workstations to attenuate the dynamics of the process flow caused the line to experience significant amount of blockage and starvation. They could not anticipate this because they used a static model of aggregated constraint capacity. These are steady-state models and cannot show the dynamic effects. A dynamic analysis was required for the job. Furthermore, they used the standard cost data from history but the activities composition was so different in the flow line that the old cost structure had no applicability at all.

Response to price pressures

The above situation is a common occurrence in any multi-product shop with high-demand variability. Static capacity models and standard costing or machine run-rate approaches to calculate individual product costs are not valid methodologies. Decisions made using these approaches will always be wrong. You may find partial successes but will never be able to tap your full potential. The activities based cost and management (ABC/M) techniques can help but only after the fact. After all, ABC is an accounting device and not a management tool to create the future. A similar situation would rarely exist in a low-variety with long-run setting. The solution requires a tool that assesses the dynamic changes in the process and the corresponding activities composition to build the resource requirements and financials for the future environment.
Profit Mapping is a tool for aligning operations with future profit and performance. It focuses on the activities performed by people and machines to improve process effectiveness and growth. Here we construct an activities composition of the process, understand the dynamics of how it changes over time, and tie this information to the resource requirements and the cost to produce products or services. As business conditions change – such as changes in product mix, demand, product or service delivery capabilities, vendor performance, business strategy, etc. – Profit Mapping reassesses the resource requirements and cost/profitability implications of the new and changed activities composition. The capability of Profit Mapping is in its ability to directly connect the controllable parameters to the business objectives within the capabilities and constraints of your organization. It is a radical yet intuitive enhancement to operational decision making process that is equally suitable from executive to shop floor decision making.
In subsequent issues of this journal I will explore with you several real-life examples of using Profit Mapping. We will identify parameters that we can control within our capabilities and constraints to reach our financial as well as other business objectives. This is one of the fundamental principles of the Profit Mapping methodology. In applying Profit Mapping we take an agnostic view towards the improvement philosophy and evaluate the consequences of decisions, irrespective of their origin or basis, from the process, resources and financial perspectives. Our focus is not on what happened in the past but to look forward to the future.
I believe the complexity in multi-product and high-variability in demand environment is immense where traditional single-focus methodologies and generic guidelines are not acceptable. A systematic approach focusing on the business goals – not on the intermediary issues such as efficiency, throughput, inventory levels etc. – is imperative.

Dr. Anil Menawat is the founder of Menawat & Co. He can be reached at or (734) 786-4065.

If My Operations are Lean, Why Bother about Scheduling Them?

By Charlie Murgiano:

“Our company is implementing Lean. Why should we worry about scheduling our operations? Why should we introduce complicated, expensive, potentially wasteful computer software? If we focus on Lean principles, why should not our factory schedule itself? Are not Heijunka (Demand Leveling) and Kanban-based shop floor control all that we really need?”

With more widespread knowledge of Lean, many manufacturing practitioners are asking themselves the above questions. The benefits of Lean can truly be amazing, and some aspects of Lean make sense in any manufacturing environment. However, in your environment, the obvious answers may not be the correct ones. In this and subsequent columns, I will review Lean scheduling and discuss where it works best and where it may not work so well. I will also review other scheduling techniques that you might want to consider if your situation warrants.

Lean principles clearly are applicable to scheduling. For instance, the Lean Thinking approach tells us to concentrate on the Value Stream viz. the steps from design through order acceptance, manufacturing, and shipping. Lean advocates view these steps as being linked together in a Flow. The Flow of product and information through the Value Stream should respond only to Pull from the customer. Finally, we should strive for Perfection viz. the reduction and eventual elimination of wasteful practices that do not add value to products or services delivered to customers.

On all shop floors, some prominent examples of waste are set-up time, travel time, time to rework defective products (or to replace scrapped products), and inventory (raw materials, work in process and finished goods). Lean Thinking helps us to attack these wastes. Through a series of kaizen (Continuous Improvement) events, we can reduce set-ups using methods such as SMED (Single Minute Exchange of Dies). We can cut travel times and distances by implementing Manufacturing Cells. We can improve quality using techniques such as Six Sigma. If we can reduce these and other forms of waste in our manufacturing processes, there is less need to hold expensive buffer inventory that in itself is wasteful.

Lean also offers us specific techniques for scheduling our factories. Demand Leveling (Heijunka) helps us to stabilize and even production flows. Heijunka takes the total volume of product requirements in a planning period and levels them out so the same amount and mix of products is being made in each production period. So, if customers order 200 Part A’s and 200 Part B’s in a 20 day month, we might make 10 A’s and 10 B’s each day.

Kanban offers us a way to schedule production through the Value Stream using Pull. In a typical Kanban-based Pull Scheduling system, there is a “supermarket” of finished goods inventory to track and measure on-hand inventories of different SKU’s. As customers withdraw a finished goods item, a physical replenishment signal, or Kanban, is sent to the upstream process that produces the item. As the process converts material, it sends a Kanban to its upstream process asking for more material. In this manner we can link all upstream processes and use Kanban signals to Pull product through the entire Value Stream. Also, we can “size” Kanbans, so that specific quantities of specific items are pulled from each upstream process. If the Kanban quantities are not one, the size of the Kanban determines WIP (work in process) inventory in the system.

So why will not Heijunka and Kanban-based Pull Scheduling work perfectly? They will, in a perfect world (or a world like Toyota’s where the techniques were originally developed). However, the world is not always perfect. A number of factors in your environment may give Lean scheduling trouble. Also, in some environments where Lean scheduling works well, other techniques may work better.

What environmental factors prevent Lean scheduling from working well? Typically, high variability on either the supply (production) side or the demand (customer) side gives Lean scheduling trouble. Variability is the enemy of level Flow. However, the beauty of Lean is that the Lean techniques discussed above relative to reducing waste, also reduce production variability, making Lean scheduling more and more appropriate. With this said, sometimes it is not possible, or otherwise economically feasible, to reduce all variability in your production processes. Also, rarely is it possible to exert total control over your customers. In some markets and market niches, reducing customer variability is impossible. If variability is high, you will need to buffer several workcenters with larger Kanban lot sizes, and greater WIP inventory, lessening the benefits obtained with Lean scheduling. In these high variability environments, is there a better way? The answer is “Yes!”

So far we have discussed how adopting the Lean philosophy can have a significantly positive impact on your business. We have also reviewed Lean techniques for reducing waste and variability in your operations, and aspects of Lean scheduling. In a perfect world, these techniques work great. However, if it is impossible to eliminate variability, you will not be able to achieve all of Lean’s benefits, and you may want to consider alternate approaches.

In the next column, we will discuss more specific examples of variability that is difficult to remove from your production processes. We will also discuss other scheduling methods not derived from the Toyota Production System that many manufacturers around the world have successfully implemented.

Charlie Murgiano is a principal with Waterloo Manufacturing Software (WMS). Prior to joining WMS, Charlie was a consulting manager at AT&T ISTEL and a manufacturing operations manager for TRW. He can be reached at or (216) 382-2541.

Cell Design for High-Mix Low-Volume Assembly

By Shardul Phadnis:

This article discusses the design of cells in high-mix low-volume assembly environments. It briefly introduces the process of cell design, highlights elements of the design process that are essential from a Lean manufacturing standpoint and then lists the challenges faced in making those elements work in a high-mix low-volume assembly environment. The article is based on the assembly of large-sized units that are moved from one location to another with the assembly work being done standing as opposed to bench assembly of smaller parts.

What is an Assembly Cell?

Assembly cells are commonly used in manufacturing facilities. Michel Baudin [1] defines an assembly cell as a set of physically linked machines or assembly stations where a family of parts is processed through a common sequence of process steps by a team of multifunction operators moving between workstations at a required pace which is autonomously controlled by the team. An assembly cell is thus a collection of different processes arranged in physical proximity to perform certain tasks – manual and/or mechanical. Operators are assigned to the cell to perform different tasks and the cell is required to produce parts at a rate fast enough to meet demand.

Several issues need to be considered while designing an assembly cell. The cell design process starts by identifying all the component parts required to build the unit and the sequence in which they are assembled. This knowledge gives information about the activities to be performed in the assembly process. These activities can typically be broken down into smaller tasks. These tasks are assigned to different workstations and/or operators within the cell such that the total workload among all workstations or operators is balanced.

Figure 1: Operator Workload Balance for Assembly Cell (graph to be loaded later)

Figure 1 shows an example of the workload balance chart for a cell with five operators. The tallest bar on this chart is the constraint operation in the cell and the cell can produce units as fast as its longest operation (Op-3 in Figure 1), which is 9 minutes. This cell would produce 1 unit every 9 minutes and this rate is called cycle time of the cell. To determine number of operators to be assigned to a cell one needs to know the demand rate for that unit. This rate is called takt time in the Lean Manufacturing literature. The cell needs to be staffed such that its cycle time is at least as much as or faster than the takt time. While assigning tasks to operators, one also needs to iteratively consider precedence of assembly tasks, location at which incoming material is supplied, and the path traveled by an operator to perform several different tasks. This information is then used for determining locations of various workstations.

The objective of cell design is to assign assembly tasks to operators, determine assembly sequence, and define locations for workstations and material while making the most efficient use of manpower assigned to the cell ex. evenly distributing the workload among all workstations, such that all the bars in Figure 1 are of fairly equal height.

Information Requirements for Assembly Cell Design:

The following information needs to be available to design cells as per the objective mentioned above:

  • Assembly bill of materials
  • Time-study data for various tasks to be performed
  • Precedence constraints for assembly tasks

Once the cell is designed to run with certain number of operators, the information on cell setup needs to be documented in a Standard Work document. Standard work is an important element of Toyota Production System (TPS) and Lean Thinking, which define it as the current most efficient way to produce product. TPS/Lean relies on following it religiously to reduce variation. The standard work document for an assembly cell would typically indicate:

  • Number of operators used in the cell and cell’s cycle time
  • Assignment of various tasks to different operators, sequence in which tasks need to be performed, and the time required to perform them
  • Location of various workstations and tools
  • Type and quantity of different types of parts required for each assembly, material delivery points, and WIP location

Challenges of High-Mix Low-Volume Assembly:

The tasks involved in design of an assembly cell require thorough study of the product typically done by a person with specialized skills such as an Industrial Engineer. In a high-volume production environment, the large amount of time spent is justified because once the cell is set up it stays in production for a long time. On the other hand, a high-mix low-volume producer does not have this luxury for two reasons:

  • The short-lived nature of the cell means the Industrial Engineers would be constantly busy designing cell setups
  • The amount of time spent by specially trained Industrial Engineers is amortized over only a small amount of product. Thus, overhead cost per unit is quite high in a high-mix low-volume environment compared to the high volume situation

Thus, high variety and low production quantities make it difficult to apply/work what is an important element of TPS/Lean in a high-mix low-volume environment.

Solution for High-Mix Low-Volume Environments:

The solution to tackle this challenge encompasses two concepts:

  • Identifying similarity among assembly tasks for different parts, and
  • Using computation power to do much of data management and processing

The decision to build certain units in an assembly cell is made based on the similarity of assembly tasks performed to build that unit, even thought the units built are quite different from each other. One needs to take advantage of this similarity – at the assembly task level as opposed to part or unit level – to tackle the challenges of high-mix assembly.

High variety also means that the amount of information to be handled is very high. Because of this, manual methods used in low-variety “lean” production environments (such as kanbans, heijunka boards, etc) are typically inadequate in high-mix production facilities, and computational tools are often necessary to manage and process data. While employing computational tools in a high-mix environment, one still needs to follow the basic principle that Lean adopts when manual methods are being used: keep things simple. The computational tool developed needs to be simple to use by performing all intricate transactions behind the screen in order that the user does not get confused or overwhelmed by the display.

Case Study:

We developed a simple computational tool for a high-mix low-volume assembly cell in a store-fixture manufacturing company. This assembly cell builds store-fixtures that are produced as per customer demand. Each fixture is unique to each customer and there are very few common parts. But, the assembly tasks involved in building different fixtures in this cell are quite common among different units. We developed a database application using Microsoft Access that takes advantage of this commonality of tasks and produces standard work instructions for designing assembly cell setups

[1] for building different units with different takt times. The typical time required for producing one cell setup is less than 30 minutes.

The work done in developing this application can be broken down into four broad phases:
Step-1: Study of the cell and product mix
Step-2: Development of basic structure, data collection, and data entry
Step-3: Training of end-users
Step-4: Development of standard work documents as needed
The work involved in the first two steps is primarily a one-time activity and is done at the beginning of the project. Step-3 is performed at the beginning of implementation and additional training can be conducted as needed. Step-4 is generation of standard work documents as needed.

The first stage of the application includes studying the production cell(s) to be served by this application. The study begins with getting a list of all the units built in the cell. Once all assemblies made in the cell are identified, the next step is to study the components that make up these assemblies and then categorize the components into different types based on the activities performed with each component. The reason for classifying different part types is to be able to list all possible activities related to each part type. After identifying all the activities, the next step is to break each activity down into different tasks performed. Time studies are then conducted to find process times for these tasks.

In the second step, a database is developed to store information on activities, tasks, time-study results, etc. The same database can be used for managing that information for developing cell setups or a separate application can be developed for that. In Step-3, the end-users of this application are trained. This included training on reading the standard document as well as some concepts of flow, such as identification of constraint, understanding takt time & cycle time, cell setup times, etc. The user needs to be trained identify skills required for different operators and assigning operators to respective positions in order to utilize their strengths. The user also needs to identify the constraint operation in the cell from operator workload balance chart so that appropriate person can be assigned to this critical position, which determines the cycle time & hence throughput of the cell.

Step-4 involves generating the standard work documents. The user has to develop a new cell setup (and print corresponding standard work document) each time there is a new unit or change in the demand rate. Once a standard work document is developed for one unit to meet a certain demand rate, the same document can be reused until there is a change in the design of the unit or any of the task times have changed due to technological or operational improvements.


In the case mentioned above, we noticed two types of benefits:
  • Improvement in cell’s efficiency as measured by units produced per man-hour
  • Reduction in cell setup changeover time between products

The improvement in cell efficiency results from better utilization of available manpower as the cell is balanced better. Variation in cell efficiency was also reduced overtime as the cell was set up and run according to a standard document. The improvement in cell setup time was also important since setup changeovers are quite frequent in high-mix low-volume assembly.


Every tool has its limitations and the application developed in the case-study is not without its own. One of the chief requirements for this application to be successful is to have a flexible cell that can be easily reconfigured as needed – both in terms of cell layout as well as breaking a job into different activities and assigning to different operators. Rigid cell layout with same level of task assignment could result in longer walking distances for the operators, which would increase cell’s cycle time due to longer processing time at the constraint, operator fatigue, etc.


This article discussed the challenges faced by implementing a lean concept in a high-mix low-volume assembly environment and presented one solution to overcome those challenges. It is important to emphasize that most of the principles of Lean Thinking or Toyota Production System can be applicable to a high-mix environment, but the methods are not. This requires us to invent new tools and methods to benefit from lean principles in high-mix low-volume environment.

Baudin, M. 2002. Lean Assembly: The Nuts and Bolts of Making Assembly Operations Flow. Portland, OR. Productivity Press, Inc. ISBN: 1563272636.

[1] A cell setup gives information about number of operators required, the assignment of tasks to operators, and locations of workstations, incoming material, and WIP units.

Shardul Phadnis is the Director of Continuous Improvement at idX-Baltimore. He can be reached at or (410) 551-3600 x2224.

How Fit Are Your Routings?

By Sidney B. Schaaf:

Before I get into the main article, I just want to take a moment to thank the originators of this journal for inviting me to become an active contributor or an “Area Editor”. I am both excited and honored to be part of a group focusing on implementing LEAN in domains beyond the Toyota Production System, particularly the high-variety low-volume (HVLV) scenarios. I suspect that ome of the unique challenges presented by the different types of jobshops and other HVLV factories which I have visited will certainly keep the ideas and discussions flowing for a very long time.

Now onto “How FIT are your routings?” At first glance, the title for this article seems quite straightforward. However, it was chosen specifically for several reasons. One reason is to point out how different people think differently. What does this title mean to you? Before you answer this question please allow me to provide you with several meanings for the word “FIT” obtained from the website:

1) To be the proper size and shape for: These shoes fit me.
2) To be appropriate to; suit: music that fits your mood.
3) To be in conformity or agreement with: observations that fit the theory nicely.
4) To make suitable; adapt: fitted the shelves for large books.
5) To make ready; prepare: Specialized training fitted her for the job.
6) To equip; outfit: fit out a ship.
7) To provide a place or time for: You cannot fit any more toys in the box. The doctor can fit you in today.
8) To insert or adjust so as to be properly in place: fit a handle on a door.

Ok, I will stop here. But be assured there are other definitions which can also apply to this three letter word.

From the numbers above, it looks like I have a one-in-nine chance or (roughly an 11% chance) to match the definition used for this article. Notice that I said I had a 1 in 9 chance, but only listed 8. Good catch, but the reason I mentioned nine is because the possibility exists that you have used a definition other than the one from the list that I supplied. Tip: Do not limit your thoughts to only what has been presented. Many times when analyzing problems, what is not being said is just as important as what has been said.

For this first installment of “How FIT are your routings?” I will be expounding upon Definition #2. Is your routing appropriate for your shop? In order to help explain the fit or whether your particular routings suit your needs, we need a basic definition that describes in minimum what routings are used for or help to accomplish. Routings serve as a step-by-step method for determining how a part or product is made. In my opinion, in addition to the part number identifying the product, here are 6 basic requirements I believe that all routings need:

1) Process step number – simply the sequence and order of making something.
2) Process type – mill, turn, move, assemble, kit, inspect, heat treat, package, …
3) Process description for each step – what is to be done for specific step.
4) Process time (a.k.a. standard process time) for a single piece.
5) Resources to be used (equipment, tools, work center, people,…)
6) Setup time for each step, including support materials like fixtures, tooling, and consumables

Again at first glance, the requirements seem straightforward. Well, let me ask: If these requirements are straightforward and to the point, why do many jobshops have issues or problems with the concept? I have provided three of the most common answers I hear from jobshop supervisors or workers as to why routings are not kept up-to-date or why there are errors associated with the routings: “My workers already know what to do when they get the parts”. “Why should I take the time to correct something that is one of a kind?” And my favorite, “If I made the part according to the prints or routing, I know it will not work.”

I believe many jobshops have grown complacent and are not making sure their routings and related documentation are updated after the job has been completed. This seems more problematic at some companies where the part is considered a one-of-a-kind.
This oversight or complacency has the makings of a future disaster.

Why do I say this? Because I have discovered that routings and software source code are very similar. I design both the electrical and software components of automation for a variety of fabricating machines used in different factory environments. Once a software routine has been written and debugged, it typically would be placed into a controlled source code library. Programming routines being placed in this library are considered gospel. Programmers accessing this library rely upon the source code to be 100% accurate and anomaly-free. When used correctly, software developers seldom have to start from ground zero, thus keeping software development costs down. Hopefully everyone can understand the importance of keeping software routines up-to-date. Routings should be treated the same way. But from what I have witnessed at many of my jobshop clients, routings still remain inaccurate in many of the jobshops that I have visited.

How many times has a one of-a-kind product come back to be manufactured again as a two-of-a-kind product? Only you can answer this question. However, I can assure you that many jobshops do get repeat business after they ship the one of-a-kind order. If the routing was never updated, building a two-of-a-kind product can be as confusing as the first time, particularly if a different person is making the part or a fair amount of time has passed since the same part was made.

Still not convinced? Try this simple test! Go to your files and pull out a seldom used routing with an average number of process steps and give it to your production workers. Ask them how much time they spend trying to figure out what exactly their involvement is during the manufacturing process. I would include the time spent searching for the supporting documentation required to help explain certain processes! I believe you will be surprised at how much actual time is spent in just clarifying the what-to-do portion of the routing. What do you think would happen if a member of your staff is new and this employee is say not at the same skill level as some of your seasoned workers? Or worse, an experienced employee retires or leaves to go and work for your competitor?

Earlier, I had mentioned the 6 basic or minimum requirements common for every routing. Here is your chance to see how FIT your routings are:

1) The sequence number is a must. This number is what establishes the correct order for manufacturing. No rocket science here. But have you considered some form of real-time tracking associated with your parts? Part numbers coupled with routing sequence numbers could provide some status information of where the part is in the overall process. Tie this information in with a specific customer order number and you could potentially provide your customer specific information regarding when their parts will be ready or where in the manufacturing process they are. Some ERP (Enterprise Resource Planning) systems already provide this feature usually as an add-on option.

2) Process type, or more commonly operation description, is a must. However, one pitfall to watch out for is simply being too general. Here is what I am referring to: I was at a company which had an operation described as MILL. Within their shop they actually had several different types of mills defined as face, end, and form. I made the suggestion that it would be clearer to assign the following 3 operation descriptions FACE MILL, END MILL, and FORM MILL. You may think this a minor change. However, in reality, by breaking up this general classification into specific functions, it actually helped their material handlers. You see their job shoplayout was divided into areas such that mills of each type were grouped together in a specific (separate) area. Shop Floor Layout is a different subject that I am not going to address. This particular jobshop had a high turnover rate for material handlers where they were promoted or simply moved into other manufacturing areas within the company.

3) Process description for each step printed on the routing is critical. Although I believe this to be a requirement, not everyone does. I have seen process descriptions rely solely upon the resource and work center fields to suffice for what needs to be performed. Although I believe this method appears to be somewhat cryptic in nature, I suppose workers can adapt and handle what has to be done by referring to these fields and remembering through sheer repetition the machine numbers and work stations for various operations. When I see this scenario in a jobshop, I point out that this is an area that can induce confusion particularly with some of the less-than-seasoned workers. However, in order to be fair with my observation regarding this shortcoming of some routings, I do have to admit that most of the travelers that accompany the parts usually give plenty of information to what exactly has to be done to complete the given process at the given time. This is something best analyzed by your production people.

4) Process time (a.k.a. Standard Process Time) for a single piece is where I see problems associated in the smaller to medium jobshops. These fields are typically left blank or do not even show up on the routing itself. When I have talked candidly with the workers at these smaller organizations, I get responses like “This time does not mean much because it is generated by someone who has no clue as to what really needs to be done”, or “We finish the job sometimes sooner or sometimes later depending upon the number of problems or emergencies that come up”. Unfortunately, this component of the routing does have a big effect throughout the jobshop but seems to be ignored by many. Why is this? I will simple respond by using Larry the Cable Guy’s line -- “GIT ‘ER DONE”.

5) Most routings that I have looked at do a reasonably good job in identifying the resources to be used. They usually tie a machine number or work center number to the step number which in turns defines the actual resource used. What most shop floor people do not know is how this resource has been chosen. I would suggest periodic review of how and why resources get assigned to which process and the steps involved. Data mining in this area would be extremely helpful for both the Operators and the Industrial Engineers.

6) When it comes to setup time, I have seen many routings simply report a time. For example, consider an actual routing describing a setup operation: Operation 180, Dept 55, W/C 1330, Mach 221, Qty 1, UM each, OPER. DESC. Setup, Crew 1, Pcs/Hr NA, Tot-Hours 0.4, User NA, Cnt NA, Reference 1/11/2004. Although there was a value supplied, how accurate is this time? Even if we examine additional information from other operation steps, which does not always, help to define what the operator has to do before they can make parts. In this example, the crew of 1 has been given 24 minutes to setup his machine to perform the next operation on the routing. Do these 24 minutes include the time required to build up a specific tool being called out on a part program listing? Does it include the time required for the operator to have a material handling system (or person) deliver the material or required tooling? Does the time also include labor required to build a fixture? I think you may be getting the idea of how important it is to not only provide the time to complete the setup but also to provide a description to the crew, which describes exactly what is to be done for the setup step.

The above discussion highlighted is what I believe to be some of the common pitfalls the small to medium sized jobshops have with their process routings. Hopefully, it will inspire some of you to take a closer look at your routings and provide you with enough information to get you thinking and enable you to answer the question “How FIT are your routings?”

Part 2 and subsequent columns on this topic will emphasize the importance of accuracy and times of your routings particularly when routings are used or tied into the following:

1) How do product costs tie to your routings?
2) How do process costs tie to your routings?
3) Do your “Process Steps or Process Types)” take into account every possible resource that can perform those steps?
4) What other uses can your routings provide?

Sidney B. Schaaf is a Senior Project Engineer at the W.A. Whitney Co., Rockford, IL. He can be reached at CODER1996@AOL.COM or (815) 761-4216.