Operational Excellence Variability & cycle time reduction

Transcription

1 Operational Excellence Variability & cycle time reduction Prof.dr.ir. Marcel van Assen 1

2 Basic Measures Throughput (TH): for a line, throughput is the average quantity of good (non-defective) parts produced per unit time. Work in Process (WIP): inventory between the start and endpoints of a product routing. Cycle Time (CT): time between release of the job at the beginning of the routing until it reaches an inventory point at the end of the routing. 2

3 Cycle Time Definition (Station Cycle Time): The average cycle time at a station is made up of the following components: cycle time = move time + queue time + setup time + process time + wait-to-batch time + delay times wait-in-batch time + wait-to-match time typically make up 90% of CT Definition (Line Cycle Time): The average cycle time in a line is equal to the sum of the cycle times at the individual stations less any time that overlaps two or more stations. 3

4 Reducing Queue Delay CT q = V U t 2 c a c e 2 2 u 1 u Reduce Variability failures setups uneven arrivals, etc. Reduce Utilization arrival rate (yield, rework, etc.) process rate (speed, time, availability, etc) 4

5 Theme s 1 What is Operational Excellence 2 Impact of variability on Operational Excellence 3 Lead time reduction as the ultimate internal performance indicator 4 Sandcone model: continuously building on the fundaments 5

6 Cycle time What is utilization? In relation with lead time (cycle time)? 6 Utilization

7 A Manufacturing Law Little's Law: The fundamental relation between WIP, CT, and TH over the long-term is: W I P T H parts parts hr Insights: hr Fundamental relationship Simple units transformation Definition of cycle time (CT = WIP/TH) Little s Law: TH = WIP/CT, so same throughput can be obtained with large WIP, long CT or small WIP, short CT. The difference? C T 7

8 Hierarchy of (conflicting) operational objectives High Profitability Low Costs High Sales Low Unit Costs Quality Product High Customer Service High Throughput High Utilization Low Inventory Fast Response Many products Less Variability Short Cycle Times Low Utilization High Inventory More Variability 8 8

9 9 What is variability?

10 Sigma = a measure for the extent to which a process is in control Sigma ( ) is een statistical measure for the distribution of a process A Six Sigma-level indicate that 99,99966% of all units (parts) are within the specifications limits, taking into account a drift of max. 1,5 Six Sigma is also a structured method to eliminate variability of a process in order to increase process control DPMO % fout % goed niveau 3,4 0,00034% 99,99966% ,02330% 99,97670% ,62100% 99,37900% ,68070% 93,31930% ,85370% 69,14630% ,00000% 31,00000% 1 10

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13 Sigma = maat voor beheerst proces 13 Sigma-niveau Aantal afwijkingen per miljoen nog steeds toelaatbaar (DPMO) ,4

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15 The relationship between utilization and lead time 15

16 The relationship between utilization and lead time 16

17 Impact of arrival variability on queues and cycle times A Aankomsten van klanten in de loop van de tijd tijd Aantal klanten in systeem A tijd In systeem A arriveren klanten met een aankomstintensiteit van gemiddeld 12 klanten per uur, maar met hoge mate van variatie Aankomsten van klanten in de loop van de tijd B Aantal klanten in systeem B tijd tijd In systeem B arriveren klanten met een aankomstintensiteit van gemiddeld 12 klanten per uur, maar met lage mate van variatie

18 Impact of variability in production systems Variability always has a negative impact on the performances of a production system 18 18

19 Influence of Variability Variability Law: Increasing variability always degrades the performance of a production system. Examples: process time variability pushes best case toward worst case higher demand variability requires more safety stock for same level of customer service higher cycle time variability requires longer lead time quotes to attain same level of on-time delivery 19

20 Variability Buffering Buffering Law: Systems with variability must be buffered by some combination of: 1. inventory 2. capacity 3. time. Interpretation: If you cannot pay to reduce variability, you will pay in terms of high WIP, under-utilized capacity, or reduced customer service (i.e., lost sales, long lead times, and/or late deliveries). 20

21 Variability Buffering Examples Ballpoint Pens: can t buffer with time (who will backorder a cheap pen?) can t buffer with capacity (too expensive, and slow) must buffer with inventory Ambulance Service: can t buffer with inventory (stock of emergency services?) can t buffer with time (violates strategic objectives) must buffer with capacity Organ Transplants: can t buffer with WIP (perishable) can t buffer with capacity (ethically anyway) must buffer with time 21

22 Buffer Flexibility Buffer Flexibility Corollary: Flexibility reduces the amount of variability buffering required in a production system. Examples: Flexible Capacity: cross-trained workers Flexible Inventory: generic stock (e.g., assemble to order) Flexible Time: variable lead time quotes 22

23 Flexibility: the effect of cross-skilled teams 23

24 Flexibility: the effect of using floaters 24

25 The use of floaters and cross skilled teams to structurally hedge for uncertainty 25 25

26 Basic Variability Takeaways Variability Measures: CV of effective process times CV of interarrival times Components of Process Variability failures setups many others - deflate capacity and inflate variability long infrequent disruptions worse than short frequent ones Consequences of Variability: variability causes congestion (i.e., WIP/CT inflation) variability propagates variability and utilization interact pooled variability less destructive than individual variability 26

27 Assignments of the workgroups during these days Analysis and redesign of your real-life process 1. Discuss eachother problem process with the help of internal and external developments regarding that process 2. Map the process on brown paper c) Describe the process with the help of the process mapping method d) Analyze the process (use real life data such as times, variances, TBV s, etc.) e) Analyze bottlenecks 3. Redesign the process on brown paper f) Generate possible solutions and rank them g) Choose and redesign the process accordingly 4. Evaluate this group-based analysis and redesign trajectory: what was good about it and what went wrong? 27

28 Theme s 1 What is Operational Excellence 2 Impact of variability on Operational Excellence 3 Lead time reduction as the ultimate internal performance indicator 4 Sandcone model: continuosly building on the fundaments 28

29 29 The positive influence of short lead times

30 Delivery reliability: Negotiating longer, more certain (?) lead times versus lead time reduction 30 30

31 Dupont scheme

32 32 Speed is crucial

33 Theme s 1 What is Operational Excellence 2 Impact of variability on Operational Excellence 3 Lead time reduction as the ultimate internal performance indicator 4 Sandcone model: continuosly building on the fundaments 33

34 Build continuously on the fundaments Sandcone-model: from effective to efficient Sustainable efficiency is only gained as a cumulative result of improvements on quality, reliability and flexibility. AND IN THAT ORDER! 34

35 Processes & quality Rework in a line r = 1/3 t = 1 1- p p 35 p = 1 y = yiled loss

36 Processes & quality Rework in a line 2/3 2/3 1- p 1 2/3 p 36

37 Redesigning an production organization via the PBOI 37

38 38 Process mapping & Rasci-model

39 Effective and efficient planning and control