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Optimizing High-Mix Low-Volume Operations

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1 Optimizing High-Mix Low-Volume Operations
Shahrukh A. Irani Department of Integrated Systems Engineering The Ohio State University Columbus, OH 43210 PHONE: (614) WEBSITE: Lean is widely popular only because the TPS (Toyota Production System) is a revolutionary, successful and globally adopted production system. But, TPS is best suited for assembly line manufacturing because it was developed by an automobile manufacturer. Toyota is a LOW-mix (they produce a limited range of highly-similar products in any one of their facilities) HIGH-volume (they produce thousands of the same car model in any year at any one of their facilities) manufacturer that uses assembly lines to produce its products. In contrast, there are thousands of SME’s like Hoerbiger Corporation of America that are HIGH-mix LOW-volume manufacturers of a wide variety of products that are ordered in LOW/MEDIUM/HIGH volumes. I started studying Lean for HIGH-mix LOW-volume manufacturers around In 2001, I obtained funding from the Department Of Defense to adopt/adapt/enhance TPS (aka Lean) for custom forge shops that are mostly, if not all, HMLV defense suppliers. The result of my research is JobshopLean, a methodology that integrates appropriate Lean tools with Industrial Engineering methods to implement Lean in HMLV facilities. One of the characteristic features of JSL is the reliance on computer-aided analytics because the popular Lean tools: are pencil-and-paper (manual) methods that cannot solve large versions of the problems that they solve --- They can easily be replaced by optimization methods that can be implemented using available software tools or computer programs written by IE/OR professionals cannot solve complex problems make us ignore important problems that jobshops struggle with

2 Agenda Types of Manufacturing Systems
What type of manufacturing system do you manage? What makes jobshops (high-mix, low-volume, MTO) different from any “Toyota-type” plant? Limitations of the (Toyota)Lean tools Examples of high-mix low-volume (HMLV) manufacturing systems CASE STUDY: Optimization of the layout of an entire plant CASE STUDY: Optimization of the setup on a press A Toolbox for High-Mix Low-Volume Manufacturers

3 Spectrum of Manufacturing Systems
QUANTITY (Volume) Assembly Lines or Transfer Lines Flexible Flowshops Manual Cells High Flexible Mfg.Cells Jobshops The two criteria that are typically used to classify manufacturing systems are Volume and Variety (Mix) Notice that the Assembly Line and the Jobshop are at extreme ends of the spectrum? Then why do we persist with implementing Lean in jobshops using many Lean tools that are primarily suited for LOW-mix HIGH-volume assembly lines? Low MIX (Variety) Low High

4 What is Your Manufacturing System?
MIX (R) QUANTITY (Q,T) Outliers P RUNNERS REPEATERS In a Part Family STRANGERS Except for the OEM’s who have repetitive assembly lines, many manufacturers are actually operating two or more manufacturing systems in the same factory and trying to manage all of them using a single combination of manufacturing strategy, workforce skills, ERP system, facility layout, etc.! How does one identify these different manufacturing systems? I use a method called PQR$T Analysis to segment the product mix of the factory. A typical PQR$T Analysis locates every product in the entire product mix produced by the factory on three axes: $ALES ($): This is how you classify your products as being Cash Cows versus Dogs VOLUME & TIME (Q,T): You study both the quantity ordered for each product and the pattern of ordering i.e. Q(t) to determine if it is a Runner, Repeater or Stranger --- You DO NOT manage all three segments the same way! MIX (R): You analyze the routings of all the products to identify how many clear-cut part families exist – One? Many? Outliers?  It is important to know the outliers because they do NOT belong in even one of the existing part families Where would products produced in an assembly facility lie and where would products produced in a jobshop lie on this 3-dimensional grid? LOW HIGH PROTOTYPES $ALES ($)

5 Lean for Toyota ≠ Lean for Jobshops
Jobshops ≠ Assembly Facilities High mix of products i.e. many different routings Part families may not be known Product mix segmentation must be done Setup times, cycle times, lot sizes, etc. vary significantly Wide variety of product designs and equipment types Typical facility has a Process Layout (= batch-and-queue) Different (and Difficult) Business Environment Demand is unstable Lot sizes change Customer loyalty and sanity are non-existent Production schedules are driven by due dates (not Takt Time) Shifting capacity constraints Due dates are different and subject to frequent changes An assembly facility and a jobshop are radically different manufacturing systems that SHOULD NOT be designed and operated using a generic set of Lean tools just because they have been passed down to us for free from Toyota

6 Many Lean Tools are NOT Universal
Strategic Planning Top-Down Leadership Motivated Workforce 5S Total Productive Maintenance Setup Reduction Error-Proofing Quality at Source Visual Workplace Right-sized Equipment Standardization of Work X Right-sized (= Inflexible) Machines X Kaizen Events (Mainly by Operators) X 20th (not 21st) Century Managers X Pencil-and-Paper Problem Solving X Value Stream Mapping X One-Piece Flow Cells X Product-specific Kanbans X FIFO Sequencing of Orders X Pacemaker Scheduling X Inventory Supermarkets X Scheduling using Takt Time X Heijunka/Load Leveling X Assembly Line Balancing USE the tools in the left hand column but DO NOT USE the tools in the right hand column. There are enough existing tools that were NOT developed at/by Toyota that could easily replace, if not are superior to, the standard Lean tools. So why don’t we learn them and use them to improve jobshops?

7 How to Recognize a High-Mix Low-Volume Manufacturing System?
A Spaghetti Diagram maps the routings of all the products that you make on the existing facility layout. It will tell you whether or not you are a HIGH-mix LOW-volume manufacturer. But it is not a trivial task to produce a Spaghetti Diagram for the product mix of any jobshop that could consist of hundreds of unique manufacturing routings! Let us now look at some examples of this simple but effective method from past projects that we did.

8 Forge Shop (≈500 Routings)
What does this tell you about the product mix and the facility layout?

9 MTO Industrial Scale Fabrication Facility
Here we mapped the complete Bill Of Routings for a complex fabricated product. What does this map tell you about the existing facility layout?

10 Flexible Machining Cell
This is a multi-product machining cell. Does it have the traditional U-shaped layout? Notice that there is no single linear material flow pathway?

11 Finish Grinding Department
HMLV manufacturers have to deal with high flow complexity instead of ignoring it. Using optimization, they can quit relying on the manual Lean tools that are incapable of visualizing this complexity and fail to suggest strategies to reduce or eliminate this complexity.

12 Factory Layout Optimization at Ulven Forging
This case study utilized optimization methods to study and improve an entire factory!

13 Current State This custom forge shop produced 450+ different forgings for commercial and defense customers.

14 Future State We could not completely convert the facility into a set of independent manufacturing cells because there were many monuments i.e. equipment that could not be relocated; so we did the next best thing and implemented partial cells around the monuments.

15 Actions Taken An additional processing area was created in the Drop Hammer building where cleaning,finishing,packaging and shipping were consolidated. The 158 ton Trim Press was replaced by a 440 ton press that was positioned next to the 5000# Hammer. This eliminated the transportation of large forgings to a distant 350 ton Trim press. Also, a 350 kW induction heater and conveyor were purchased and co-located with this press to form an Upset Forging cell. A new 2.5” Upsetter was purchased and positioned next to the 3000# Hammer to form an Upset Forging cell. By implementing CELLS based on the concept of part families, Ulven Forging agreed that only a major layout change would allow them to reduce travel distances and promote teamwork.

16 Actions Taken (contd.) The 1.5” Upsetter was replaced with a faster machine and positioned next to the 700 ton Press to form an Upset Forging cell. A crane was installed over the 5000# Hammer to reduce piston change-out time, reduce die key tightening time and to facilitate product movement in the area. A portable Marvel Hacksaw and 1.5” Bar Shear were acquired. A CNC Mill was acquired and positioned next to the EDM machine to reduce vendor costs and lead times for die sinking. (CONTINUED FROM PREVIOUS SLIDE) By implementing CELLS based on the concept of part families, Ulven Forging agreed that only a major layout change would allow them to reduce travel distances and promote teamwork.

17 Benefits Approximately 5% cost savings on annual sales of $ 6 million
WIP reductions were significant Lead times quoted to customers were reduced Throughput ($ales) increased Since this company is a defense supplier, they were reluctant to release financial and delivery performance data that could be seen by their customers (Defense Logistics Agency and Department Of Defense)

18 Press Setup Optimization at Hirschvogel
In the previous case study, we looked to optimize the entire factory; in this case study, we utilized optimization models to study and improve workflows at a single forging press in an effort to reduce its setup time

19 Observe and Document the Press Setup
SMG 14 is one of the “workhorses” at Hirschvogel’s facility in Columbus, OH

20 Work Locations around the Press
This is a list of all the locations around the press that the video showed the operator visiting and working at throughout the setup process.

21 Sequence of Tasks in Press Setup
This spreadsheet captures the entire sequence of 225 steps that constitute the setup of the press. Each step is performed at one of the locations around the press that are listed in the previous slide.

22 Operator Motion Traffic around the Press
PFAST, one of the optimization packages that we use at OSU, converted the 225-step setup process into this aggregated traffic matrix between all pairs of locations around the press.

23 New Workstation Layout for the Press
STORM, another one of the optimization packages that we use at OSU, took the From-To Chart produced by the other package and generated this conceptual solution for how the work locations around the press ought to be re-arranged.

24 Operator Motion in Previous Layout
This is how the operator moved during the setup process BEFORE we did our optimization study.

25 Operator Motion in New Layout
This is how the operator moved during the setup process AFTER we did our optimization study.

26 Press Setup Time: Before vs. After
Activities Current Process Redesigned Process Difference No. Time % Operations 247 1:32:07 71% 235 1:28:53 79% -12 -0:03:14 Inspections 32 0:11:28 9% 31 0:11:23 10% -1 -0:00:05 Transport. 135 0:17:54 14% 92 0:12:45 11% -43 -0:05:09 Storage 0:00:00 0% Delays 12 0:09:01 7% -0:09:01 Total 426 2:10:30 100% 358 1:53:01 -68 -0:17:29 IN ADDITION, we did a classical Time and Motion Analysis of the entire setup process which helped us to reduce the time per setup done on this forging press by 17 minutes. So how did this time saved per setup benefit Hirschvogel? Simple! Use the capacity that was freed up to produce more forgings and sell them to make more money! How did we do this? Capacity that was already available on the press had now become available. So Hirschvogel could afford to do more setups even if they had to lose some of that freed up capacity to do the extra setups. But there was sufficient leftover capacity that could be utilized to make more forgings!

27 Estimation of Increased Production
Potential Increase in Production = [EPT – (# of Setups * Time/Setup)] / Cycle Time per Part Relationship between Number of Setups and Number of Parts Produced (of same type) that could be produced using the Extra Production Time (EPT)

28 Estimation of Increased $ales
Potential Increase in Revenue = [EPT – (# of Setups * Time/Setup) / Cycle Time per Part] * $/Part Relationship between Number of Setups and Revenue from Extra Production that could be earned (based on various part prices) using the Extra Production Time (EPT)

29 Benefits Savings in Setup Time Potential Increase in Revenue Category
Initial Proposed % Decrease Setup Time (min) 130.5 60.86 53.3% Number of Activity Steps 426 358 16.0% Distance travelled by Operator (steps) 1167 797 31.70% Potential Increase in Revenue Part # Demand Price/ Part Revenue A1234 6,000 $ $ ,300.00 B3456 3,300 $ $ ,100.00 D6755 7,500 $ $ ,750.00 Extra Parts 16800 Extra Revenue $ 210,150.00 The setup reduction project freed up enough available capacity whereby more setups could be done to process additional/extra orders because, despite losing some of the freed up capacity in setups, there was still time left to make forgings to complete the additional orders

30 Parallel Task Scheduling for Press Setup
1 Operator min (Current State) 2 Operators min (Parallel Execution of Activities) 3 Operators min (Unnecessary, 2 operators are OK) Gantt Chart for Optimized 2-Person Setup Process Op #1 Op #2 We even utilized a project scheduling algorithm that told us that we could convert a sequential one-person setup process into a parallel two-person process which could be completed in HALF the time compared to the original setup

31 Optimization could Enhance Every Lean Tool
Why do I use use optimization to enhance and extend the Lean tools? Because the manual pencil-and-paper Lean tools have handicapped and limited HMLV manufacturers from achieving significant gains that could be earned by solving complex Continuous Improvement problems using optimization-aided methods!

32 Multi-Period Slotting of Orders
Value Stream Mapping Demand Forecasting Multi-Period Slotting of Orders Work Order Release Current Project at Pompano Beach Warehouse Design In this slide, using a Value Stream Map obtained from the Learning To See book, I have shown all the areas of any manufacturing system for which optimization models have been successfully developed to design, analyze and improve each of those areas. Scheduling Supplier Deliveries Cell Design Work Center Scheduling WIP Inventory Control Scheduling Material Handlers

33 A Toolbox for HMLV Manufacturers
“4H” LEADERSHIP Walks the Gemba Knowledgeable Beyond TLSS Competitive Respects Employees Efficient Fire Fighters (Risk Managers) Change Managers Invested in Talent and Technology ENGAGED WORKFORCE Lean Thinkers “Factory of One” Problem Solvers Empowered Multi-skilled Team-oriented IT Savvy Collaborative FUTURE STATE CURRENT STATE MORE…. COMPETING THROUGH INNOVATION Value Network Mapping M3 Facilities Flexible Focus (GT) Product Mix Segmentation ERP+FCS+MES IT-enabled JIT Communications Virtual Cells and Distributed Teams Water Striders Real-time Order Tracking PLM+CAPP Agile Suppliers UNIVERSITY PARTNERSHIPS Co-Curricular Projects Co-ops Internships Faculty R&D Executives on Loan Factories as “Test Beds” INDUSTRIAL ENGINEERING Work Measurements Facility Layout Ergonomics Scheduling Variety Control Value Analysis/Value Engineering DFMA Flexible Mfg. Cells Product/Process Standardization Product Mix Rationalization etc. LEARNING ENTERPRISE Cafeteria Chats E-newsletter Wikis Kaizens Online Chat Groups Idea Boards Annual Conference Resource Center - E-books - Case Studies - Videos - Online Apps - etc. Why the conveyor representation for a manufacturing enterprise? Because every wheel needs to be working in order for the conveyor to work and carry items forward from one end to the other. Any HMLV manufacturer like Hoerbiger Corporation of America needs to be doing many things correctly and well in order to go from good to great!

34 Acknowledgements The PRO-FAST Program is enabled by the dedicated team of professionals representing the Defense Logistics Agency, Department of Defense and industry. These team mates are determined to ensure the Nation’s forging industry is positioned for the challenges of the 21st Century. Key team members include: R&D Enterprise Team (DLA J339), Logistics Research and Development Branch (DLA – DSCP), and the Forging Industry Association (FIA).

35 Acknowledgements Project Champion: Craig Kaminski
Project Engineer: Haydn Garrett Project Champion: Kevin Shaw Project Engineer: Greg Muniak Project Champion: John Wilbur Project Engineers: Thomas Slauta Project Champion: Dick Johnston Project Engineer: Todd Sheppard Jon Tirpak Russell Beard Vicky McKenzie Project Champion: Joe Kracheck Project Engineer: John Lucas Project Champion: Andrew Ulven Project Engineer: Jim Huiras Dan Gearing Project Champion: Thomas Stys Project Engineer: Jorge Alvarez PFAST Development Team Dr. Rajiv Ramnath Dr. Rajiv Shivpuri

36 Questions?

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