Where do you want to work? If you’ve ever been to Disney or Epcot you may remember the experience. You park your car or get off the tram and you don’t need to be able to read a map, or the signs, you just follow the walkways and it just seems obvious where to go and how to get there. A ton of science goes into making the experience at the Magic Kingdom completely different from that of the traveling carnival that shows up at the edge of town in the empty lot next to the volunteer fire house. At the carnival you can’t get from here to there, if you even can figure out where there is. Kids may have a bunch of fun at either, but the parental stress level is completely different between the two amusement parks.
Which of the two do you want your office or shop floor to be like, Disney or the carnival? If Disney is your destination, how do you get from here to there?
- Information is the output of an office. Information can take many forms: email, databases, presentations,decisions.
- Wastes of Defects, Storage, Motion, Overprocessing, Waiting, Overproduction all occur in much the same ways as on a factory floor. For example motion can be seen in walking, reaching, searching, questioning, interrupting. Each of these activities cause delays and stress. But we adapt and accept and live with the abnormal. We just get used to it.
- Time is the inventory of the office. Time piles up in our in-boxes and databases. Time happens when work stops. We run out of information, need a signature, find a mistake and then set that work aside and pick up some other job, file, task. We keep busy. But the thing we were working on sits and waits, the clock ticking away.
Making the abnormal viable, finding where the time is piling up isn’t easy, but that’s the mission of the visual office; making the piles of time visible, and then once we can see the inventory of time we just might get uncomfortable and creative and go do something to reduce the inventory, and speed up the flow.
Here are a couple references …
 
 Simulation is the act of imitating or mimicking the behavior of some situation or some process by means of something suitably analogous. The imitation of a process can be used for debugging, and validating process design changes or use to communicate or train associates.
Simulations can be used for:
- process design
- testing new ideas
- debugging designs
- testing understanding
- gaining commitment
- testing alternatives
- communicating and training
Sometimes the simulation is role playing theater, other times the ‘game’ has logic and is reproducible, with known inputs and expected outputs. The photo here is of a recent workshop where we studied how the warehouse dock floor would look after changing the pick waving rules and packaging. Here outbound goods will be switching from trailer loose stack to returnable shipping containers.
Would we need more floor space? Do we have enough pickers and loaders? How do we pick and load multiple deliveries nose-to-tail?
While computer modeling is certainly a consideration the use of table-top simulation has many benefits:
- Many problems are difficult or expensive to test in real life
- Many people process information visually
- A number of alternatives can be quickly tested as the team uncovers issues and finds solutions
- Simulation costs are very low; you don’t need expensive software or extensive training
Here’s the process we used to build our ‘war game’:
- Decide what we wanted to test; i.e. the output – in this case floor loading and labor resources
- Gather the input – shipping orders for a typical busy day, number of pickers by zone, number of packing loaders, shift schedules, picking and loading rates, floor space and equipment dimensions (carts, containers, trailers, etc)
- Determine the constraints, rules; e.g. number of loaders per trailer, length of breaks
- Document assumptions; e.g any trailer can be at any dock door, break and lunches can be staggered, etc.
- Be creative and design the game pieces (entities) and determine their quantities; in this exercise carts, containers, bins, trailers
- Scale physically (1inch=5feet), scale time (1 day of 10 hours took an hour of game time)
- Collect metrics, such as; line per hour, wave start and end time, trailer load duration, number of floor spaces occupied, number of time floor space turned over, number of workers needed
Once the model ‘behaved’ like the current process the team began introducing rule changes which uncovered obstacles. One of the first changes was reducing the wave batch size from 90 minutes to 30. Next came changes to packaging and trailer loading. By the end of the workshop new procedures were debugged and ready for full scale dry runs leading to a live implementation next month. Stay tuned …
Euclides A. Coimbra and his associates at the Kaizen Institute have created a wonderful and detailed work on the application of continuous improvement to supply chains. Here is a full exploration and application of lean from end to end of the extended value stream. Two thumbs up!
Some of the graphics look to once have been powerpoint and when reproduced are to small and grainy to be able to read. There isn’t an index so finding topics is limited to the table of contents. The book is hard bound, and printed on good paper.
Some of the vocabulary is odd; “border of line” might be better said as” interface” or “borderline”.
Economic Order Quantity, or as referred to in this book, Wilson’s Formula, is treated in a refreshing way.
We can say that Wilson’s formula still applies today. The only problem is when people assume that changeover time (or, generally speaking, ordering cost) is rigid and cannot be reduced. Many people don’t think to do Wilson’s calculations because they are still misled by two strong paradigms: flow at any cost and efficiency at any cost.
The ‘flow at any cost’ paradigm is a rising paradigm that is currently gaining in popularity. People hear about the wonderful Toyota Production System (TPS) and start to increase the flow by reducing the batch sizes blindly, without looking at Wilson’s formula. What happens is that the CAPEX requirements explode, because the small batch sizes together with big changeover times decrease efficiency. The result is that flow is indeed achieved – but at the expense of capital expenditure, not by internally reducing the changeover time and increasing equipment flexibility. You can see this effect in many rich companies that are implementing Lean manufacturing and the TPS.
For a more in depth review check out Jon Miller’s posting on Gemba Panta Rei,
Review of Total Flow Management by Euclides Coimbra.
Hot off the press from the Lean Enterprise Institute …
Page 12 & 13 have a brief description of Coefficient of Variation and a SKU Scatter Diagram (weekly volume vs. SKU stability). 10 weeks usually isn’t sufficient for meaningful or statistically significant calculation of standard deviation.
The guidelines given need to be tempered with the granularity of the data. While a coefficient of variation of less than 1.0 can be considered stable for weekly data, it would be considered very noisy when using monthly data and quite stable when using daily demand.
This small quibble aside the authors Martichenko and von Grabe do a wonderful job describing lean principles for the supply chain, or as they prefer, the fulfillment stream.
Determining an appropriate production model starts with Demand Profile and Demand Segmentation. High volume low variability items, and low volume high variability items behave very differently. How to decide if a particular product is a candidate for a one piece flow cell or a craftsmen job bench? Look to the coefficient of variation for a clue.
Type 1 – Rate-base or Just-in-time
- forecasting of the flow rate or takt time
- RCCP – rough cut capacity planning to monitor impact of mix and volume on pace maker operation
- produce to rate (or TAKT) vs discrete order or customer pull
- demand flow vs time-phased requirements planning
- maintain flow priority and timing
- no detailed Capacity Requirements Planning required
- no or minimal shop order launch or inventory transactions
- highly visual and standardized shop floor control
- “one-piece” flow, zero inventory, standard WIP – work-in-process
- seamless flow/pull of material
- Dynamic cycle time (Little’s Law)
Type 2 – Pull
- combination of discrete forecasting and/or demand rate-based forecasting
- MRP planning — pull Kanban, Heijunka visual shop floor control
- RCCP, but no detailed CRP
- flat Bills Of Materials
- more cellular manufacturing
- point-of-use vs. central stores
- inventory is strategic: standard inventory, time-based replenishment, pull based on consumption vs. push based on demand
- based on statistically balanced rate, build to level-loaded demand with calculated standard inventory buffers
Type 3 – Push or Job Shop Discrete
- discrete requirements planning (firm orders and long range forecast)
- Rough Cut Capacity Plan
- time phasing of requirements
- application of order policies: lead time, safety stock & time
- Capacity Requirements Planning
- MRP shop order launch & order maintenance (message filters and “noise management”)
- ability to aggregate disparate requirements across multiple products by work center, supplier, product
- central stores of inventory
- multi-level inventory: stores, pick, kit, move, queue
- batch processing
- demand leveling difficult and uneconomical
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