Lean Sigma Supply Chain » Definitions

Overall Plant Effectiveness

Lawrence Loucka — Sun, 27 Dec 2009 22:44:48 +0000

The Eight Major Plant Losses

Shutdown
Production adjustment
Equipment failure
Process failure
Normal production loss
Abnormal production loss
Quality defects
Reprocessing

Waterspiders as continuous improvement innovators

Lawrence Loucka — Tue, 08 Sep 2009 11:34:14 +0000

The term Waterspider or water beetle (mizusumashi in Japanese) comes from the behavior of the insect known in the States as a whirligig, an aquatic animal that skitters around on the top of a pond quickly changing direction as it goes. For a lean enterprise the role of material handlers, expediters, and support staff changes. In the Toyota Production System this is the common name for a person assigned to support a production operation, so that others may focus exclusively on value-added work. The waterspider delivers parts to the other associates in the cell or on the line so that they don’t need to stop to replenish their work stations.

Unlike a ‘floater’, a waterspider is assigned specific tasks, such as replenishing raw material inventories (via milk run), common area clean-up, communicate status, maintain visual metrics, etc… Waterspider duties usually don’t include tasks which take them away from the production area, or detract from their specific, assigned duties (the waterspider is not the ’5S’ person or a ‘fill in’). Think of the waterspider as the ‘race car pit crew’ for the production team, without which it would be impossible to win or even run the race.

Waterspiders quickly become experts in the withdrawal and production kanban system. They can ‘see’ more of the up and down stream flow in real time than most others, and because of this often making it possible to identify and eliminate errors. From recent experience the waterspiders often have a better grip on reality than their managers, planners, and engineers.

Non manufacturing examples abound in restaurants, hospitals, insurance claims processing; serving the folks that add the value isn’t just for manufacturing. In product and software development the role of the program manager is sometimes something like that of the waterspider, except bringing knowledge to the various development team members instead of parts.

Here are a few references:
Single piece flow at ConMed Linvatec
Improving Workflow With Water Spiders at University of Michigan Health System
Inventory management in electronics manufacturing: The Move To Lean
Lean in the Oil Fields

Have any examples you’d like to share?

How to calculate Total Landed Cost?

Lawrence Loucka — Mon, 17 Aug 2009 10:28:49 +0000

There’s the math, and then there’s the data collection effort. First the math:

Purchase Price:

Price paid to seller (which may include some of the following)
INCOTERMS
Payment terms
Exchange rates over time

Transportation and Logistics:

Foreign inland
Line haul
U.S. inland
Accessorials
Insurance
Packaging

Customs and Imports:

HTSUSA (tariff) rate
Merchandise processing
Harbor maintenance fee
Broker fee
Less: Duty Drawback

Inventory Costs:*

Cycle stock
Safety stock
Inventory in-transit

*Inventory costs can vary depending on the INCOTERMS in category 1 (when does ownership of the inventory change) and the way a company values its inventory.

Overhead and Administration:

Sourcing and Supplier Quality staff
Due diligence
Relationship building/travel
Learning curve

Risk and Compliance:

Compliance costs (technology, staff, other)
C-TPAT program costs
Channel Master carbon footprint mandate compliance costs
Insurance costs
Cost of potential risk of supply disruption
Cost of potential risk of damage to reputation Health, Safety, Environment

Did I miss any?

To this add trends and forecasts for the drivers of these factors. Such things as labor rates, social costs, fuel, cap and trade, currency exchange rates. After all it’s tomorrow’s total landed cost that we’re after.

Next, the data collection plan …

Lean Sigma Tools for Supply Chain, part 2

Lawrence Loucka — Sun, 09 Aug 2009 15:28:51 +0000

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

Lawrence Loucka — Sat, 08 Aug 2009 00:24:15 +0000

Not all of the lessons from Toyota and Motorola translate well into health care, project management, product development, services but many easily do. Here’s a partial list for supply chain. Have any additions, comments, or examples to share?

**Lean Sigma Tools for Supply Chain**
Lean Sigma Tool	Definition	Supply Chain Application
Brainstorming	Generate a wide range of ideas around any topic.	Why not get the warehouse pickers together from time to time to engage them in a discussion on safety, accuracy, or productivity improvements?
Affinity diagrams	Sort the post-its in to logical groups, and give each cluster a name.	Start or end of shift crew meetings can have a team problem or improvement board. Sorting suggestions, brainstorm ideas, or process defects in a public forum is a great way to engage the warehouse or office.
Multivote	One way to prioritize or narrow down a list of alternatives.	Instead of the squeaky wheel, or the boss’ mandate, allowing the folks to set their own priorities for continuous improvement is one way to foster engagement and buy-in.
Process mapping	Come in a variety of styles: flow charts, swimming lanes, spaghetti, etc. A visual model of the process.	Helpful training aid. For many a flow chart is easier to comprehend than a standard operation procedure text.
Process observation	Gain a deep understanding of a process in action by planning what you want to capture and how you plan on doing it. Most processes have too much going on all at one to be able to ‘see’ what’s really happening, so we focus on one ‘actor’ at a time and usually start by watching what happened to the product or service, then is a separate session observe the machines or technology, and then only after really understanding product and process to we observe the people and what they are doing. Reason? People are almost always victims of the processes and products others designed.	In supply chain there are a number of challenges. First hurdle is recognizing that there is a process. What is the product or service supply chain provides? Is it movement of goods or processing of information or both?
SIPOC	Supplier, Inputs, Process, Outputs, Customer – a visual table or chart to help define process boundaries and stakeholders.	Every new WMS or TMS project should start with a charter, project plan and a SIPOC to get all the players calibrated on who is who and why. Surprising the confusion often found around understanding who the customer is and what happens up and down stream.
Spaghetti map	Stable yourself to a order or component and follow it through the process, always enlightening, often embarrassing when plotted on a facility layout	Pick path maps often show problems: location inaccuracies, split lots, poor slotting. Your WMS may direct traffic, even if it does it can be worthwhile to follow a picker around and watch for dead ends, reversals, treasure hunts.
Swim lanes	Flow chart arranged with rows or columns to show functional handoffs.	From customer order through sourcing, planning, scheduling, receiving, putaway, pick, pack, ship the number of times the order and product are touched, adjusted, queued, handed off, and acted on is the start at recognizing waste and variation in supply chain management.
VA Analysis	Breaking down a process into activities and then deciding if the customer would think each task was valuable.	Most of Supply Chain is non value added. Just moving product from here to there doesn’t change the product. Some will argue that the end customer is willing to pay to move product, so any activity that doesn’t move the product closer to the customer is waste. Does the customer care if you have to inspect the paperwork, or put the pallet in and out of a rack?
7 Wastes	A way to categorize non value-added activities and help us see waste: overproduction, defects, transportation, waiting, inventory, motion, processing. Also known as ‘muda’.	Overproduction – unnecessary packaging Defects – inventory record errors, shipping damage, mislabeled Transportation – shipping from the wrong DC Waiting – queuing up orders Inventory – excess, slow moving, obsolete Motion – rearranging a split pallet, reaching for supplies Processing – unnecessary tasks
Check sheets	Simply a list of tasks, hopefully unambiguous and logically sequenced. A memory aid.	Wouldn’t want an airplane pilot to take off with out running through the preflight checklist, why conduct a physical inventory without one?
Frequency plot	Also known as a histogram. Helps to see the distribution of a set of data. A statistical tool.	More picking errors on small orders or large, or early in the shift or at the end? Collect some data and plot it to find out.
Measurement System Analysis	Statistical study to determine if the accuracy of an measure is adequate.	Many warehouses have labor productivity goals or standards. How accurate and reliable is the record keeping? If the case pick to powered pallet jack is standard 52 lines an hour should a picker be concerned about achieving only 50, or feel great about hitting 54?
Total Productive Maintenance	An approach to maximizing the effectiveness of facilities used within a business. Total productive maintenance, or TPM, aims to improve the condition and performance of particular facilities through simple, repetitive maintenance activities. Based on a culture of teamwork and consensus, TPM teams are encouraged to take a proactive approach to maintenance. A team is made up of operators and those involved in the setting up and maintenance of the facilities.	Got to keep the lifts running, batteries charged, printers printing … Does equipment downtime ever become an excuse? Don’t let the equipment decide when to take a break, schedule the maintenance on your own terms. Factories have figured this out why not the warehouses?
DMAIC	Project planning mnemonic – define, measure, analyze, improve, and control	Why not use this outline on any change initiative?
FMEA	Failure Modes and Effects Analysis – often used in postmortem, best used to prevent.	Better to anticipate what could go wrong with the new WMS installation than to have to deal with the clean up after the meltdown.
Gemba	Go see. Don’t theorize from the front office, instead to to where the issue, problem, value lives and look at it.	Looking in the racks, using the white glove test (how thick is the dust on the slow moving stock?), observing the housekeeping is all part of the visual management and servant leadership culture of lean sigma in supply chain.

Warehouse Zoning

Lawrence Loucka — Thu, 06 Aug 2009 01:45:28 +0000

A technique for laying out warehouse storage which seeks to minimize “pick” travel time by grouping the most used items closest to their point of use.

Walter Shewhart

Lawrence Loucka — Wed, 22 Jul 2009 18:36:02 +0000

Dr. Shewhart was a prominent scientist with the Western Electric Engineering Department back in the 1920s. In 1924, Dr. Shewhart devised a framework for the first application of the statistical method to the problem of quality control. Shewhart wrote a note to R.L. Jones, responding to his request for some type of inspection report that “might be modified from time to time, in order to give a glance at the greatest amount of accurate information”. He attached a sample chart “designed to indicate whether or not the observed variations in the percent of defective apparatus of a given type are significant; that is, to indicate whether or not the product is satisfactory.”

Shewhart’s example was the world’s first schematic control chart. In one short letter, he had set forth the essential principles and considerations of quality control. As he pursued this work, Shewart gave birth to the modern scientific study of statistical process control.

In 1931, Shewhart’s book ‘Economic Control of Quality of Manufactured Product’ contained his findings on statistical sampling techniques. A Western Electric colleague, W. Edwards Deming, spread the word on Shewhart’s work when he joined the US War Department, and later when he taught the fundamentals of quality in Japan.

Frederick Taylor

Lawrence Loucka — Wed, 22 Jul 2009 18:09:32 +0000

Taylor, Frederick Winslow (1856-1915), American industrial engineer, who originated scientific management in business. He was born in Germantown (now part of Philadelphia), Pennsylvania. In 1878, he began working at the Midvale Steel Company. He became foreman of the steel plant and applied himself to studies in the measurement of industrial productivity. Taylor developed detailed systems intended to gain maximum efficiency from both workers and machines in the factory. These systems relied on time and motion studies, which help determine the best methods for performing a task in the least amount of time. In 1898 he became joint discoverer of the Taylor-White process, a method of tempering steel. Taylor served as consulting engineer for several companies. His management methods were published in The Principles of Scientific Management.

Facility Block Layout

Lawrence Loucka — Mon, 06 Jul 2009 16:16:15 +0000

A standard approach for creating a new production facility layout for either a green field or an existing facility is as follows:

Perform PQ Analysis
Preparing a Product Process Routing Matrix
Develop Block Layout alternatives
Optimize the size, shape, placement of the blocks.
Nimawashi

PQ (Product Quantity Pareto ABC Analysis) and Product Process (find common routings in a mixed model business) are defined elsewhere. For many practitioners Block Layout seems be be either a bit of artistry or is mired in software complexities. Here are a few thoughts on how to approach this step in the facility design process.

First a few considerations:

In a green field we know the product and process and want to determine the size of the building we need and it’s layout. For a brown field we’re trying to make the best use of the use of the four walls we already have. In both scenarios there are trade offs to make. Having a decision making at the beginning of the project can save a lot of time and money. Some will take a mathematical approach, others organic consensus. Either way agree on the design process methodology up front.

Determine “best” layout type based on customer demand, product and processing characteristics, and business strategy. Common layout types include:

process functional – group common machines or processes together
product – line up equipment in sequence of operation
fixed position – for large projects where you can’t move the product
hybrid – mixed model, shared monument, group technology cells

In brown field facilities the main layout consideration is often in fact moving from one layout type to another as business conditions and strategies evolve.

Determine the activity and proximity relationships between the various blocks. A great approach for understanding relationships is the Simplified Systematic Layout Planning method by Muther and Wheeler.

The Product Process Routing Matrix noted above determines the quantity and type of equipment needed. One complication is that very expensive or large machines may need to be shared, so compromises may need to be made. I like the table top trial and error Paper Doll approach. Once we’ve gathered data on the importance of proximity and activity relationships between blocks, equipment footprints, maintenance and material handling access and clearance requirements, utilities, building codes, facility constraints, etc. and then we determine the gross footprint size. Now through trial and error we arrange the equipment in the block in a logical flow or sequence manner. We then have a beauty contest and subject each alternative to a decision selection matrix where we score and rank various design factors such as compactness, adjacency (relationship closeness), least travel distance (material handling cost and speed), etc.

The number of permutations can be huge, so either use group intuition for the block details or investing in one of the current software packages such as Pro Planner, PlanOpt, Flow Planner.

More Kanban Calculations

Lawrence Loucka — Fri, 22 May 2009 13:13:46 +0000

First listed various formulations of calculating kanban quantities in July 2006. Here are a few more …

9. wmarhel at Elsmar Cove writes …

The formula for calculating the number of kanban cards in a system for a particular product is:

(Daily Demand x (Run Frequency + Lead Time + Safety Time)) / Container Capacity

Where:

Daily Demand = Customer Consumption expressed as # of units
Run Frequency = Frequency which you decide to set-up and produce that item. This is expressed as a unit of time. For a five day work week, running the product every day would equal (1), every third day would equal (3), etc.
Lead Time = Manufacturing lead time (processing time + Set-up time + queue time) + lead time for kanban retrieval expressed as a unit of time.
Safety Time = Allowance for variations in demand and supply, also expressed as a unit of time. Keep as low as possible.
Container Capacity = Number of units per container (# of units in a container is always the same number).

10. World Class Manufacturing has an on-line Kanban Size Calculator that uses the following formula:

Total Required Inventory (TRI) = Weekly Part Usage * Lead-time * Number of locations for stock
# Kanban = TRI / Container Capacity

11. Oracle uses

By default, the standard calculation is:

(C – 1) * S = D * L

where:

C is the number of kanban cards
S is the kanban size
D is the average daily demand
L is the lead time (in days) to replenish one kanban

12. SAP says …

K = ((RT * AC)/CONT) * (SF + C)

where

K numbers of Kanban
CONT contents per Kanban
RT replenishment lead time per Kanban
AC average consumption per time
SF safety factor
C constant (default 1)