1. Kenneth J. Andrews EMP-5179-6-1 Gen-X: Manufacturing Analysis What is the process?Build & test of AXIS machine for a specific Customer Who is the customer?MegaPower- product quality - install time - on-time delivery - ship what ordered - good training Installation- complete shipment - documentation - tested, working - acceptance test OK - early notification

2. Kenneth J. Andrews EMP-5179-6-2 Gen-X: Manufacturing Analysis – Flowchart (1) 1. Order is logged in 2. Scheduled by the Manufacturing Manager (remote board) 3. Order sent to Manufacturing Engineer 4. Wait for drawings – always 5 days late 5. Initiate system build (before designs arrive) 6. Designs are checked, mistakes noted – no direct feedback 7. Problems with designs – try to reach designer  WAIT 8. Mfg. Engineer modifies the designs (inventory-driven) 9. Supervisor takes the new designs 10. Systems are re-worked to account for actual designs 11. Parts are requested from Stores  WAIT 12. Problems during build  Mfg. Eng  Mfg. Mgr  Eng. Mgr  13. System hardware completed 14. System moved to Test

3. Kenneth J. Andrews EMP-5179-6-3 Gen-X: Manufacturing Analysis – Flowchart (2) 15. Chase software from Design  WAIT 16. Software arrives (late) 17. Hardware functional check – problems fixed – no feedback 18. Software check – patches for bugs – documentation? 19. No time for Acceptance Test 20. System moved to shipping dock 21. Install Coordinator advised about imminent ship

4. Kenneth J. Andrews EMP-5179-6-4 Gen-X: Manufacturing Analysis – Flowchart (1) 1. Order is logged in 2. Scheduled by the Manufacturing Manager (remote board) 3. Order sent to Manufacturing Engineer 4. Wait for drawings – always 5 days late 5. Initiate system build (before designs arrive) 6. Designs are checked, mistakes noted – no direct feedback 7. Problems with designs – try to reach designer  WAIT 8. Mfg. Engineer modifies the designs (inventory-driven) 9. Supervisor takes the new designs 10. Systems are re-worked to account for actual designs 11. Parts are requested from Stores  WAIT 12. Problems during build  Mfg. Eng  Mfg. Mgr  Eng. Mgr  13. System hardware completed 14. System moved to Test

5. Kenneth J. Andrews EMP-5179-6-5 Gen-X: Manufacturing Analysis – Flowchart (2) 15. Chase software from Design  WAIT 16. Software arrives (late) 17. Hardware functional check – problems fixed – no feedback 18. Software check – patches for bugs – documentation? 19. No time for Acceptance Test 20. System moved to shipping dock 21. Install Coordinator advised about imminent ship

6. Kenneth J. Andrews EMP-5179-6-6 Process Improvement What process? Customer + requirements Map current process Identify hot-spots Root-cause analysis Improvements to a) fix root causes b) meet C requirements Metrics (1-3 months) Communicate plan Implement, measure, fine-tune

7. Kenneth J. Andrews EMP-5179-6-7 Manufacturing Systems: EMP-5179 Module #6: Manufacturing Metrics Dr. Ken Andrews High Impact Facilitation Fall 2010

8. Kenneth J. Andrews EMP-5179-6-8 EMP-5179: Module #6  Sigma, Variance, SPC etc. Revisited  Factory Physics  Balanced Scorecard

9. Kenneth J. Andrews EMP-5179-6-9 Variability The world tends to be bell-shaped Most outcomes occur in the middle Fewer in the “tails” (lower) Fewer in the “tails” (upper) Even very rare outcomes are possible (probability > 0) Even very rare outcomes are possible (probability > 0)

10. Kenneth J. Andrews EMP-5179-6-10 Number of Samples Process Spread/ Variability Mean Process variability is determined by US

11. Kenneth J. Andrews EMP-5179-6-11 Number of Samples Specification Tolerance Mean Upper Specification Limit (USL) Lower Specification Limit (LSL) Specification tolerance is defined by the Customer

12. Kenneth J. Andrews EMP-5179-6-12 Tolerance Limits

13. Kenneth J. Andrews EMP-5179-6-13 Variation in Process Output Due to Random Causes

14. Kenneth J. Andrews EMP-5179-6-14 Low Process Capability

15. Kenneth J. Andrews EMP-5179-6-15 High Process Capability

16. Kenneth J. Andrews EMP-5179-6-16 We can be much more specific about process capability by measuring the process variability and comparing it directly to the required tolerance. Common measures are called Process Capability Indices (PCIs) μ= mean σ= std. deviation USL= Upper Spec. Limit LSL= Lower Spec. Limit Process Capability Indices

17. Kenneth J. Andrews EMP-5179-6-17 Process Capability C pk = min USL – μ 3σ μ - LSL 3σ 14 20 26 15 24 24 – 20 3(2) = =.667 20 – 15 3(2) = =.833

18. Kenneth J. Andrews EMP-5179-6-18 C pk measures “Process Capability” Good quality:defects are rare (C pk >1) μ target

19. Kenneth J. Andrews EMP-5179-6-19 C pk measures “Process Capability” Poor quality: defects are common (C pk <1) μ target If process limits and control limits are at the same location, C pk = 1 C pk ≥ 2 is exceptional.

20. Kenneth J. Andrews EMP-5179-6-20 EMP-5179: Module #6  Sigma, Variance, SPC etc. Revisited  Factory Physics  Balanced Scorecard

21. Kenneth J. Andrews EMP-5179-6-21 Factory Dynamics: Batch Production Consider a simple 4-station production line, where the processing time at each station is exactly 1 minute Batch Size (WIP) Cycle Time (minutes) Throughput (pieces/minute) Throughput (pieces/hour) 10400.2515 9360.2515 8320.2515 7280.2515 6240.2515 5200.2515 4160.2515 3120.2515 280.2515 140.2515

22. Kenneth J. Andrews EMP-5179-6-22 Factory Dynamics: Single-Piece Flow Consider a simple 4-station production line, where the processing time at each station is exactly 1 minute Batch Size (WIP) Cycle Time (minutes) Throughput (pieces/minute) Throughput (pieces/hour) 140.2515 240.5030 340.7545 441.0060 551.0060 661.0060 771.0060 881.0060 991.0060 10 1.0060

23. Kenneth J. Andrews EMP-5179-6-23 Production Throughput

24. Kenneth J. Andrews EMP-5179-6-24 “Decrease Inventories” A factor of variability Lower WIP = Less Throughput = Not Good

25. Kenneth J. Andrews EMP-5179-6-25 “Reduce Variability AND Inventories” Reduced variability Lower WIP + Reduced variability = Higher Throughput = Good

26. Kenneth J. Andrews EMP-5179-6-26 Self-Paced Study Review and research the following material relating to: SCV Availability Factory Physics Confirm your understanding by following the examples provided.

27. Kenneth J. Andrews EMP-5179-6-27 Objective Measure of Variability For example, an assembly operation with an average process time of 20 minutes and a standard deviation of 1 minute: scv = (1/20) 2 = 0.0025

28. Kenneth J. Andrews EMP-5179-6-28 Availability Consider a workstation that operates an average of 70 hours before it must be shut down for maintenance, lasting 10 hours.

29. Kenneth J. Andrews EMP-5179-6-29 Optimal Maintenance Intervals? Infrequent maintenance: 70 hours on, 10 hours off Frequent maintenance: 3.5 hours on, 0.5 hours off What about variability? Isn’t that important too?

30. Kenneth J. Andrews EMP-5179-6-30 0.028 Optimal Maintenance Intervals?

31. Kenneth J. Andrews EMP-5179-6-31 Optimal Maintenance Intervals? scv = squared coefficient of variation m r = mean time to repair A = availability t 0 = original processing time

32. Kenneth J. Andrews EMP-5179-6-32 Optimal Maintenance Intervals? Infrequent maintenance: 70 hours on, 10 hours off Frequent maintenance: 3.5 hours on, 0.5 hours off For the same equipment availability, shorter repair times lead to lower variability i.e. they are better

33. Kenneth J. Andrews EMP-5179-6-33 Utilization: High or Low?  One way to improve Return on Investment (ROI) is to maximize the revenue generated by utilizing production resources to the fullest extent possible = high capacity utilization.  Is a 24/7/52 factory a good strategy?  It depends on whether you are striving for shorter cycle times  It also depends on whether you are living in a: deterministic (ideal) world = very low variability stochastic (real) world = moderate/high variability

34. Kenneth J. Andrews EMP-5179-6-34 Cycle Time, Utilization & Variability High Variability Low Variability 20% 50% 100% Cycle Time Capacity Utilization Moderate Variability Standard & Davis: “Running Today’s Factory”

35. Kenneth J. Andrews EMP-5179-6-35 Causes of Variability  Equipment downtime  Excessive set-up time  Uneven production demand  Batch material movement  Non-standard processes  Human factors  Supplier problems  Unexpected outages (e.g. power) 1.Reduce variability wherever possible throughout the production process. 2.Do not strive for 100% capacity utilization.

36. Kenneth J. Andrews EMP-5179-6-36 Balanced Scorecard Perspectives

37. Kenneth J. Andrews EMP-5179-6-37 Preparation for Next Week  Watch for new articles/links on the website  Download material for module #7