Lean Sigma Tools for Supply Chain, part 2

Here are a few more lean and six sigma tools that can be applied in supply chain.  Have any additions, comments, or examples to share?

Lean Sigma Tools for Supply Chain
Lean Sigma Tool Definition Supply Chain Application
Location Checksheet A common visual quality data display in manufacturing is to take a product drawing and make a mark or place a sticky dot on the location of a defect or touch up.  After a period of time you’ll often see clusters.  Then we use good old Pareto and focus our team based problem solving skills on the areas of interest. Plotting the physical location of inventory accuracy errors can often be a clue for getting to the bottom of and eliminating a significant source of wasted time.  Similarly marking the location of packaging damage can help identify problems with overhang, pallet specification, strapping, and handling.
Sampling Manufacturing process and quality engineers have been taking product and process samples for over 50 year as a routine part of statistical process control or designed experiments.  100% inspection is actually less accurate in quality control than is a well designed sampling plan and the use of descriptive statistics.  As an aside the US Census could stand to use more sampling and less door to door canvasing. A full physical inventory count or ‘stock take’ is also less accurate that a well designed cycle counting program.  But even a cycle counting program is a waste of time if the errors discovered aren’t studied for root cause and permanent corrective action taken.  Whether its an annual full inventory or a daily cycle count if all we do is adjust ‘the book’ then we aren’t doing anything to improve our future.
Statistical Distributions The widely known ‘bell shaped curve’ of the normal distribution is often a good approximation of the spread we find in machining operations.  Paint thickness, electrical resistance, tensile strength can vary plus or minus around a mean or average.  Descriptive statistics such as mean and standard deviation help us understand and describe the behavior of the systems we are studying. Caution Will Robinson.  Playing with statistics without the proper training can be dangerous.  Real example: when calculating safety stock and expected inventory we often need to consider the supplier lead time.  Like any variable measurement there is always some spread, the expected 10 days could be 9 days or 15.  Lead time is almost never bell shaped.  Suppliers are rarely early. So which distribution to use? Find a good black belt and give’m a job.
Control Charts Control Charts are how we display the behavior of a process and help process operators decide when to make an adjustment, stop the process, or start an investigation.  We plot data taken from periodic samples and then follow SPC rules to determine if there has been a change in the process since the last sample. Kanban are containers or cards used to control the replenishment, supply, production of product.  The number of Kanban in circulation can be calculated based on the average consumption, replenishment time, and container size.  A single card or container then has an expected lifecycle from empty to empty.  By periodically sampling the time the container last passed through a ‘tollgate’ we can get an early warning on shifts in demand or replenishment time, hopefully in time to avoid a stock out.
5 Whys First impressions are sometimes wrong, so when we are brainstorming or investigating a situation we’ll ask about the cause of the cause of the cause.  A method for pushing our thinking beyond superficial solutions that don’t really solve the problem. Took 20 minutes to get started picking this morning.  Why? Because the printer was jammed?  Why was the printer jammed?  I guess the rollers were dirty.  Why where the rollers dirty? … You get the idea?  We keep asking Why until we get to something we can do something about like adding a weekly printer maintenance task to our TPM schedule and assigning responsibility for doing it.
Pull Systems Trying to predict (forecast) what to make and when is tough to do in many industries.  Toyota found great advantage in only making what was needed when needed, that is to replenish only what was consumed.  Ideally a supplying operation would hand off one piece at a time to the down stream consuming operation.  But when supplier and customer can’t be in close physical proximity we need some way to communicate what is needed and when.  2 Bin, kanban, FIFO flow lanes are just a few types of pull systems common in manufacturing. Some have tried using pull thinking in distribution inventory management, only replacing stock at customer facing warehouses when product is shipped out (Toyota accessories for example).  The traditional approach is to forecast the demand and then make or buy a batch large enough to cover the future demand, and hope you didn’t plan too much or too little.  Pull works well in some industries and not at all in others.  Most warehouses regardless of industry can use pull techniques for resupply of packaging, fresh pallets, wave picking period.

Lean Sigma Tools for Supply Chain, part 1




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