Steve Beeler

You have a goal…I have a way to get you there.

Lean Thinking

5S

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Lean thinking is not just for factories. 5S is an easy to implement process to organize any workplace. With a little pro bono coaching, my new friends at Holland Physical Therapy have completed their first 5S project. Here’s how we did it:

5S

We started out with this quick one-page lesson in 5S, the seven wastes, and Plan-Do-Check-Act. As you might expect from its name, 5S is a five-step process. It is a pathway to a clean, uncluttered, organized workplace reducing waste and improving productivity:

1) Sort
2) Set In Order
3) Shine
4) Standardize
5) Sustain

Introducing the seven wastes (defects, overproduction, transportation, waiting, inventory, motion, and over processing) sharpened the focus on waste reduction. Introducing the Plan-Do-Check-Act continuous improvement cycle reinforced 5S as on on-going, every day commitment, not a one-time event.

Next, with a shared understanding of terminology and principles, we did a quick walk through of the clinic. Five of the seven wastes seemed to apply the clinic’s lack of organization…we could not find examples of overproduction and over processing. Cleanliness was not an issue. However, the Holland Physical Therapy team was greatly concerned about not finding something when needed and the time wasted looking for it.

The cable column was selected as the initial application area.

We first sorted through the area and set aside what was not needed. Then we organized and labeled everything used at the cable column. Masking tape was used to temporarily identify parking spots for the many accessories. The team agreed to sustain the cable column 5S through an end of day tidy up: anything out of place would be put back to where it belongs. After a day or so, the team assessed the area, made improvements, and moved onto the next 5S application area. P-D-C-A.

5S Group Photo

Through 5S, the team at Holland Physical Therapy is on their way to better utilize their space and easily find what they need when they need it.

Variation and Waste

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Variation is at the root cause of almost all waste in manufacturing and business systems.  It is no coincidence then that variability reduction is the foundation for the Toyota Production System (Lean Thinking) and its success in continuously reducing waste.  Two games of chance with dice and cards illustrate the linkage between variation and waste.

The first game is a single piece flow system with five machines.  The output of each machine is represented by the total of two dice.

The average of two dice, of course, is 7.  However, our five-machine system only averages 4.3…a 38% loss!  Why?  Variation and waste.  In single piece flow, no machine can outproduce another.  Production is lost through waiting losses (blocks and starves) when the machines interact with each other.  Balanced and dependent systems are surprisingly common.  They never work as expected.  In isolation yes, in combination no is a key lesson from Theory of Constraints.

The second game is a system of three machines feeding an assembly area.  The output of each machine is represented by the draw from a deck of cards.  In order to assemble a product, all three cards must match.

Variation and Waste

Each machine is produces one card per time period.  Jokers represents a defective product and cannot be matched.  The decks are shuffled so the three output sequences are independent.

Variation and Waste

Quite a few cards collect (to the right of the decks) before there are matches for the assembly machine to assemble (to the left of the decks).  Work in process inventory (WIP) and lead time are horrendous.  Throughput suffers as the assembly area waits for matches.  In isolation, each machine is successfully producing cards.  In combination, the system is performing poorly.  Variation and waste again.  This time the variation is in sequence, but the waste is equally dramatic.

Variability reduction is a big part of my day job as a Professional Engineer.  Visit my Operations Engineering page for methods and case studies.  While variation is always present, robust systems can be designed  to minimize the linkage between variation and waste.

Lean Thinking in NASCAR

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Toyota may have only been racing in NASCAR for the last decade or so, but the principles of the Toyota Production System have been in the sport since its inception. Here are some examples of lean thinking in NASCAR, that uniquely American form of motorsport:

Lean Thinking
NASCAR Pit Stop

Single-Minute Exchange of Die (SMED). A pit stop is the NASCAR equivalent of a die change in manufacturing. Quite a bit gets done in only a few seconds: tires are changed, gasoline is dumped in, and chassis adjustments are made. A number of lean thinking techniques are utilized in a NASCAR pit stop:

(1) Separate Internal from External Setup Operations. Most of the work performed in a NASCAR pit stop is actually done while the car is on the track: tires are mounted, balanced, and set to the right inflation pressure; gas cans are filled up; adjustments are discussed over the radio; and everything (and everyone) is organized along the pit wall.

(2) Convert Internal to External Setup. Lug nuts are glued to the wheels so that they do not have to be positioned before being secured. Special tools have been designed for things that are frequently adjusted for changing track conditions (track bar, wedge, etc).

(3) Adopt Parallel Operations. One person could perform all the operations in a pit stop…but a carefully coordinated team can do it much faster. Everyone in a NASCAR pit stop has a job to do…and does it with very little wasted motion.

NASCAR engine bay
NASCAR Engine Bay

Countermeasures for Zero Breakdowns. Mechanical reliability in NASCAR is excellent. With the exception of a few cars too damaged in wrecks to continue, almost all the cars that start are running at the finish. All five Total Productive Maintenance (TPM) countermeasures for breakdowns are readily evident:

(1) Cleaning, lubricating, and bolting. The cars are meticulously assembled and then receive lavish amounts of attention during a race weekend. A small fluid leak will only get worse. Brake dust could be hiding a problem.

(2) Adhering to proper operating procedures. Detailed checklists coordinate and control everyone and everything that touches the car.

(3) Restoring deterioration. Virtually all parts are inspected between races. Many, like engines, are replaced after every race.

(4) Improving weaknesses in design. NASCAR teams have rigorous engine dyno programs to improve engine reliability. Redundancy is provided for systems with less than 100% reliability: electronic ignitions, batteries, etc.

(5) Improving operations and maintenance skills. Self evident…the cars get faster and more reliable every year. A very high level of organization is required to run a NASCAR team.

Shigeo Shingo and Junior Johnson would have had a common language in lean thinking…

Here are two books from my library on TPS and TPM:

“A Study of the Toyota Production System” by Shigeo Shingo (the famous green book)

“Introduction to TPM” by Seiichi Nakajima

Addendum – February 18, 2022

While watching a bit of last night’s Daytona 500 twin qualifying races, I noticed another example of Lean Thinking in NASCAR…centerlock wheels.  The new “mono lug” forged aluminum wheel is example of another common SMED technique: Use Functional Clamps or Eliminate Fasteners Altogether.

An image comparing NASCAR 5 lug and mono lug wheels

Centerlock wheels are nothing new in motorsports but NASCAR has always raced on 5 lug steel wheels.  The rules change to forged aluminum centerlock wheels reduces the number of fasteners (and time) required to remove and reinstall a wheel.

Dumping in fuel may now be the “bottleneck” in a NASCAR pit stop (pun unintended).  It will be interesting to see how pit strategies are affected.

Spaghetti Diagram

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spaghetti diagram

A spaghetti diagram provides a visualization of the flow of material and/or people through a manufacturing or business process. A spaghetti diagram is primarily used to visualize transport and motion, two of the seven wastes in lean thinking.

A spaghetti diagram is easy to construct. The most important input is process knowledge. Assembling a small team is a great idea, especially if the process of interest spans multiple departments. Not much else is needed: a plant layout or schematic, colored pencils or felt tip pens, and maybe some sticky notes.

Start at the first step of the process. Where does this material go next? What happens when it gets there? Be sure to capture decision points. For example, defects go to a rework station before moving to the next process step. I like to use red for transport (e.g., forklift moves or conveyors) and blue for motion (e.g., picking, placing, stacking). Use whatever colors work best to visualize your process.

A spaghetti diagram is a qualitative tool. To make the analysis more quantitative, you can measure distances, take process times, count forklift moves, etc. There are no rules, use whatever metrics best quantify your process.

After establishing a baseline of the actual process flow, use a future state spaghetti diagram to visualize the benefits of plant and office rearrangements, capital investments in new or additional equipment, etc.

Here is a case study. A manufacturer was ramping up production of a new product line. Additional capacity was planned but where are the best locations for the new equipment?

Current State Spaghetti Diagram

The team was very surprised by the amount of transport in the current state spaghetti diagram. There were long red lines everywhere…a plate of spaghetti indeed!

Alt #3a Spaghetti Diagram

Future state spaghetti diagrams were developed for layout alternatives with the new mold cells and assembly cell, the two planned capacity investments. It was quickly seen that an additional curing oven (not in the capacity plan) would dramatically reduce transport distances and forklift moves: the red lines are fewer and shorter.

A spaghetti diagram is a simple and effective method to analyze and compare plant layouts. Put one in your Plan-Do-Check-Act tool continuous improvement kit.

 

 

 

Balanced and Dependent Systems

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The ten machine puzzle in my Theory of Constraints blog post is a simple example of the balanced and dependent systems that are surprisingly frequent in the real world. Balanced because all elements have the same capacity. Dependent because events at one element affect the performance of other elements. Frequent because lean thinking drives people and organizations towards them.  None work very well.

balanced and dependent systems

How does this happen? Inventory, conveyance, motion, and over production are wastes that are relatively easily recognized and reduced. When these wastes are removed, waiting losses (blocks and starves) can replace them. In the extreme, system performance deteriorates as lean “improvements” are made. In isolation yes, in combination no is a primary lesson from Theory of Constraints.

There are three options to improving balanced and dependent systems. The first is to improve the reliability of all of its dependent elements. That is lean thinking, but perfection is a high hurdle. In the ten machine puzzle, each machine’s reliability must be improved from 98% to 99.8% to achieve the 98% system availability target.

Cumulative probability predicts that the perfection hurdle gets even higher for larger balanced and dependent systems. Take a process with 100 dependent steps, not unusual in manufacturing or business. If each element has a 98% reliability, the system will only be available 13% of the time. To achieve 98% system availability, the reliability requirement for each element is 99.98%. Ouch!

The second option is to oversize each of the process elements. In the ten machine puzzle, oversizing each machine from 50 to 60 units per hour does the trick. With 100 process steps, each machine would have to be oversized by almost a factor of three…now that is expensive waste!

The third (and by far the best) option is to decouple process elements with buffers and to unbalance capacities to create a distinct constraint. This option trades inventory and conveyance waste against overproduction and waiting. The trick is to find the optimum balance. Is the trick magic? No, not with discrete event simulation…the next blog’s topic.