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1 1

2 SYSi 2983 XA Best Practices in Manufacturing Execution Mike Canik Sr. Manufacturing Consultant Paper-Less, LLC 2

3 An excellent source of information to help Cope with a changing landscape Demand Management in Discrete Industries: Order to Delivery Excellence November 2007 Demand Management: Bridging External Market Inputs with Internal Statistical Forecasting June

4 And another Factory Physics: Foundations of Manufacturing Management Wallace J. Hopp And Mark L. Spearman Irwin / McGraw-Hill Publishers 4

5 What are the pressures you face? 5

6 How do you compare? 6

7 How do companies respond? 7

8 The more things change. WAIT!! WHADDYA MEAN!? What happened to last years list? All those things like inventory accuracy, turns, past due orders, on-time delivery, Lean, etc.. etc etc.? We just started working on those issues and now there s another list?!?!? 8

9 The more things change Product life cycles are shrinking. Decision time frames are compressing. Competitive pressures are coming faster than ever and usually from unexpected/new directions. Customers are becoming more and more impatient. Speed has become the new currency of business. 9

10 the more they stay the same! Every morning in Africa a gazelle wakes up knowing it must outrun the fastest lion or it will be killed. Every morning in Africa a lion wakes up and knows it must run faster than the slowest gazelle or it will starve. It does not matter if your are a lion or a gazelle, when the sun comes up, you better be running! 10

11 the more they stay the same! You must understand that in today s business world it s not the big that eat the small. it s the fast that eat the slow. and you better wake up running! Your challenge. to figure out how to deliver real value using all the tools and information you have. And then get it all done by yesterday! 11

12 Do you know how fast you are? The truth of the matter is, most don t really know 12

13 Manufacturing Best Practices Lead Time Reduction Focus Manufacturing cells (Focused Factories) Associate Engagement Strategic Inventory Reduction Cross-Functional Teamwork Equipment/Process Reliability Quick Changeover High-Performance Leadership Continuous Improvement In-Process Quality Optimal Shift Schedule Standard Operating Procedures Goal Deployment Visual Management Systems Plant Safety, Loss Prevention & Organization Incentives, Rewards & Recognition Problem-Solving Capability Cross-training & Multiskilling Supplier Partnerships World-Class Performance Measures 13

14 But the only Best Practice that matters is to.. MAKE MORE MONEY 14

15 So we need to think in those terms Goldratt taught us to look at EVERYTHING in manufacturing as a form of money. Throughput the rate at which money is generated by the system through sales Inventory all the money that the system has invested in purchasing things it intends to sell Operating expenses all the money that the system spends to turn inventory into throughput 15

16 But more importantly We need to remember the old saw that says TIME IS MONEY 16

17 Understanding, Managing, and Reducing Cycle Times 17

18 In our Manager s Toolkits We generally have several KPI s, like Efficiency Utilization Productivity Quality Etc., etc., etc. These all help us move in the right direction, right? 18

19 What makes a good KPI? From Forrest Breyfogle s book Integrated Enterprise Excellence Volume II: Business Deployment : Business alignment: Metrics consume resources for both data collection and analyses. Metrics need to provide insight to business performance, its issues, and its needs. Honest assessment: Creating metrics so that the performance of someone or an organization will appear good has no value and can be detrimental to the organization. Metrics need to be able to provide an honest assessment, whether good, bad, or ugly. 19

20 What makes a good KPI? Consistency: Identified components in any metric need to be defined at the outset and remain constant. Criteria and calculations need to be consistent with respect to time. Repeatability and reproducibility: Measurements should have little or no subjectivity. Actionability: Often measures are created for the sake of measuring, without any thought as to what would be done if the metric were lower or higher. Include only those metrics that you will act on; that is, either remove a degradation problem or hold the gain. When the metrics response is unsatisfactory, organizations need to be prepared to conduct root-cause analysis and corrective or preventive actions. 20

21 What makes a good KPI? Time-series tracking: Metrics should be captured in time-series format, not as a snapshot of a point-in-time activity. Time-series tracking can describe trends and separate special-cause from common-cause variability in predictable processes. Predictability: A predictability statement should be made when time-series tracking indicates that a process is predictable. Peer comparability: In addition to internal performance measurements, benefits are achieved when comparisons can be made between peer groups in another business or company. A good peer comparison provides additional analysis opportunities, which can identify improvement possibilities. 21

22 The Best KPI s are Customer-Centric That is, they focus on those things that affect your customers buying decisions. These tend to have the most direct bearing on revenue. Quality Lead times Delivery reliability Etc. 22

23 Do traditional measures work? How does an efficiency metric relate to the customer? How does utilization contribute to my ability to deliver on time? If I improve my productivity by 20%, what happens to my quality? 23

24 Common Mistakes Metrics for the sake of metrics (not aligned to business results) Too many metrics (no action) Metrics not driving the intended action Lack of follow up record of methodology benchmark Underestimation of the data extraction effort 24

25 Should I include Cycle Time in my Manufacturing Scorecard? 25

26 Manufacturing Cycle Time Defined: The cycle time of a given manufactured item is the average time from the release of a job at the beginning of a routing until it reaches an inventory point at the end of the routing. Is this the same as lead time? No. This is just a portion of the total order-todelivery cycle time, and may not include long waits for parts. 26

27 How predictable is your shop floor? Other functions like product design are governed by physical laws. The design requirement is for a car that entails A mass of 1,000 kg, for comfort and safety Acceleration from zero to 60 (ax. 2.7 meters per second squared), for sportiness An engine that generates no more than 200 newtons (approx. 45 pounds) of force, for fuel efficiency Can it be done? Remember, F = ma 200 N << (1,000 kg)(2.7 m/s 2 ) = 2,700 N No Way! Hopp and Spearman, Factory Physics,

28 But factories aren t quite as deterministic as that A senior VP of manufacturing demands that a printed circuit board (PCB) factory produce: 3,000 PCB s a day With a lead time (from order placement to receipt of goods) of not greater than 10 days And a service level (percent of jobs delivered within the lead time) of at least 90 percent Can it be done? This time, it s not so clear. 28

29 Easy to answer if we have the data 29

30 Basic Factory Dynamics An excellent source of information and understanding is Factory Physics: Foundations of Manufacturing Management Wallace Hopp and Mark Spearman Irwin/McGraw Hill 30

31 Trouble signs What s the cause of these symptoms? A sudden increase in late shipments A sudden decrease in total shipments Regular failure to meet published lead times 31

32 Sometimes we know right away Labor shortages Critical equipment down Material shortages 32

33 but sometimes we don t Business seems to be good, and volume is growing. This is a REALLY bad time to have these issues. What could be up? 33

34 Fundamental issues There are some basic elements to manufacturing processes that we deal with every day that we don t always think of when problems pop up. There are relationships on the factory floor that operate just like laws of physics. 34

35 Everybody knows that Throughput (TH) is the quantity of non-defective parts produced per unit of time. Work in Process (WIP) is inventory between the start and end points of manufacturing Cycle time (CT) is the time between releasing a job to manufacturing and when it reaches an inventory point at the end of manufacturing. 35

36 Law #1: Little s Law The fundamental relationship between throughput, work-in-process, and cycle time is TH = WIP/CT or WIP = TH x CT So if I know two, I can solve for the third. If TH is 100 units per day and WIP is 500 units, then CT is 5 days. Almost too simple! 36

37 Easy to imagine in a balanced system with no Process time = 8 hours = Cycle time 37

38 Start our system with just one unit to produce Process time = 8 hours = Cycle time 38

39 Start our system with just one unit to produce Process time = 8 hours = Cycle time 39

40 Start our system with just one unit to produce Process time = 8 hours = Cycle time 40

41 Start our system with just one unit to produce Process time = 8 hours = Cycle time 41

42 Start our system with just one unit to produce Process time = 8 hours Cycle Time = 8 hours Throughput = 1 piece every 8 hours, or.125 pieces per hour 42

43 The second piece changes to Process time = 8 hours Cycle Time = 8 hours Throughput = 2 pieces every 8 hours, or.250 pieces per hour 43

44 The third piece changes to Process time = 8 hours Cycle Time = 8 hours Throughput = 3 pieces every 8 hours, or.375 pieces per hour 44

45 and the fourth piece takes us to a full line with no WIP the ideal state Process time = 8 hours Cycle Time = 8 hours Throughput = 4 pieces every 8 hours, or.50 pieces per hour 45

46 Charting the Results Critical WIP (W 0 ) CT = Process Time (T 0 ) 46

47 Charting the Results Critical WIP (W 0 ) Bottleneck rate (r b ) 47

48 Law #2: Best Case Performance The minimum cycle time (CT best ) for a given WIP level, w, is given by CT best = T 0, if w<= W 0, otherwise w / r b The maximum throughput (Th best ) for a given WIP level, w, is given by Th best = w / T 0, if w <= W 0, otherwise r b 48

49 Law #3: Worst Case Performance The worst-case cycle time for a given WIP level, w, is given by CT worst = w T 0 The worst-case throughput for a given WIP level, w, is given by Th worst = 1 / T 0 49

50 And finally As utilization approaches unity, cycle time approaches infinity. WHY? 50

51 The point is.. There are relationships on the shop floor that afford a measure of predictability when conditions change. If we watch what s happening, we can manage the situation instead of having the situation manage us. 51

52 But the ideal state usually doesn t stay that way very long hrs small hrs Large hrs Med hrs 52

53 And our flow isn t as simple 53

54 So how do I keep an eye on things? First, report real-time execution with a Manufacturing Execution System like Paper-Less MES. Then, monitor your activity regularly to spot deviations from the norm or deteriorating conditions An increase in late shipments A drop in total production Cycle time changes Infor XA gives discrete manufacturers a wealth of information to support this 54

55 The available data in XA The MO master and MO history files contain a lot of valuable data, but accuracy degrades if not collected real-time Item detail Item, revision, warehouse, quantity, etc. Customer job (maybe) Dates! Create date, first/last activity date, scheduled / actual start, due date / order complete date, etc. Enables measuring for lateness and cycle times 55

56 Power-Link makes it simple! Create a view over either Manufacturing Orders or Manufacturing Order History Subset to get the exact data you want Export to clipboard or file Move to Excel or other package for further analysis Charting Statistical analysis Mean. Std deviation, etc. 56

57 Power-Link 57

58 Order Complete Date Start Lateness* Completion Lateness** Planning Cycle Time*** Planned Order Cycle Time**** Actual Order Cycle Time***** Item MO # Order Qty Scheduled Start Actual Start Order Due Date Create Date 3424 M /8/2001 2/21/ /2/2001 3/1/2001 2/7/ M /28/2001 3/1/2001 7/27/2001 3/7/2001 3/1/ M /8/2001 2/28/ /2/2001 3/15/2001 2/28/ M /17/2001 7/17/2001 7/26/2001 7/31/2001 7/17/ M /23/2001 7/20/ /12/2001 8/6/2001 7/19/ M /8/2001 1/4/2001 1/16/2001 3/1/2001 1/4/ M /1/2002 2/28/2002 2/28/2002 3/31/2002 2/26/ AA810 M /4/2001 9/25/ /2/2001 9/10/2001 8/21/ AA810 M /23/ /6/ /2/2007 3/23/2007 1/6/ Average: Metrics * Actual Start minus Scheduled Start ** Completion Date minus Due Date *** Actual Start minus Create Date **** Due Date minus Scheduled Start ***** Completion Date minus Create Date 58

59 By Item or Item Family Order Complete Date Start Lateness* Completion Lateness** Planning Cycle Time*** Planned Order Cycle Time**** Actual Order Cycle Time***** Item Average Actual CT Item Order Qty Scheduled Start Actual Start Order Due Date Create Date /8/2001 2/21/ /2/2001 3/1/2001 2/7/ /28/2001 3/1/2001 7/27/2001 3/7/2001 3/1/ /8/2001 2/28/ /2/2001 3/15/2001 2/28/ /17/2001 7/17/2001 7/26/2001 7/31/2001 7/17/ /23/2001 7/20/ /12/2001 8/6/2001 7/19/ /8/2001 1/4/2001 1/16/2001 3/1/2001 1/4/ /1/2002 2/28/2002 2/28/2002 3/31/2002 2/26/ AA /4/2001 9/25/ /2/2001 9/10/2001 8/21/ AA /23/ /6/ /2/2007 3/23/2007 1/6/ Average: Metrics * Actual Start minus Scheduled Start ** Completion Date minus Due Date *** Actual Start minus Create Date **** Due Date minus Scheduled Start ***** Completion Date minus Create Date 59

60 More detailed analysis shows Op Seq No. Work Center Std Labor Hours Actual Labor Hrs Scheduled Start Actual Start Sched Complete Actual Complete Start Complete Lateness Lateness Queue / Wait Time Efficiency 0010 MILL /23/2012 7/20/2012 7/24/2012 7/21/ % 0020 WASH /27/2012 7/23/2012 7/28/2012 7/24/ % 0030 GRIND /29/ /5/2012 7/30/ /6/ % 0040 GRIND /2/ /22/2012 8/3/ /23/ % 0050 WASH /4/ /5/2012 8/5/ /12/ % Planned Cycle Time Actual Cycle Time Planned Value Added %: 22.78% Actual Value Added %: 2.04% 60

61 What does this tell us? What is at the root of our long cycle time? What contributes to long times? How much will it help cycle times if I improve efficiency by 20%? What measures can I take to reduce my cycle times? (HINT: Little s Law) 61

62 Another KPI to consider Use lateness (positive and negative) in addition to more traditional tardiness measures, for Manufacturing orders Operations And, as always, customer shipments Also, consider KPI s that relate to factors that drive your customers to do business with you! 62

63 Questions and Comments? 63

64 64

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