Steve Beeler

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

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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.

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…

Source Inspection for Zero Defects

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As the highest form of error proofing, source inspection for zero defects is such a powerful concept that it merits a close look.

Source inspection is 100% inspection, not statistical sampling, for causal factors that lead to defects. Defects are prevented through immediate action to remove causal factors. While this may sound complicated, it is not. In fact, examples of source inspection are everywhere around us.

The logic behind source inspection is pretty simple. Before completing an action of some kind, check for causal factors of defects. If causal factors are present, then the action is stopped before completion, and before the defect occurs.  With the causal factor(s) removed, the action can be restarted and completed without creating a defect.

Source Inspection

Everyday examples are all around us:

Automobiles. A little fender bender in a crowded parking lot is a defect that we can all do without. Possible causal factor: foot off of brake pedal. Source inspection: all vehicles with automatic transmissions have a safety interlock that requires the driver to have their foot on the brake pedal before shifting out of park.

On-line forms. In this case, the defect is missing information on an airline reservation, a catalog purchase, or whatever. Possible causal factors: error of omission or typographical error. Source inspection: if a required data entry field is empty, incomplete, or in the wrong format, the reservation or ordering process will not advance to the next screen until the field is filled correctly.

Thermocouples. A residential natural gas explosion would be a very bad defect. Possible causal factor: no pilot light. Source inspection: gas water heaters, furnaces, fireplaces, and so on have thermocouples. If the pilot light is on, the thermocouple is hot and gas is allowed to flow. If the pilot light goes out, the thermocouple cools down and shuts off the gas flow.

Does source inspection make statistical sampling and control charts obsolete?  Absolutely not.  Use statistical process control to reduce causal factor variability to minimize interruptions and increase productivity.

Zero Defects

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In high-volume manufacturing, are zero defects achievable? For every dimension on every part in a complex assembly, probably not. But for key customer characteristics, a qualified yes.

A qualified yes because zero defects require 100% inspection but not all types of inspection can reduce and ultimately eliminate defects. Just working harder will not achieve zero defects…you also have to be very clever about it.

For a statistically stable process with a high capability, the chance for a defect caused by common cause variation has been practically eliminated to less than one chance in the millions. This is a fine achievement. However, no amount of hard work can repeal the second law of thermodynamics. Entropy, or disorder, is always increasing…this is why leaves blow into your garage, not into lawn and garden bags. Defects can and will be produced by even the best processes.

Statistical sampling and control charts cannot guarantee that all defects will be detected. The second law ensures all stable processes will eventually be visited by a special cause and will produce defects. If the special cause is continuous, defective products produced since the last good sample will have to be found and repaired. If a special cause is intermittent, defects may or may not be found in the sampling plan.

Zero Defects

Judgment inspection discovers defects and separates the good from the bad. Defects are contained but neither reduced or prevented. A quality system relying on judgment inspection tolerates in-system defects and their effects on downstream processes. Forever. Judgment inspection deserves its bad reputation as a low value added activity.

Informative inspection investigates the cause of defects and feeds the information back to the source. Defects are reduced but the quality system is still tolerant, to a lesser degree, of in-system defects. The effectiveness of informative inspection is proportional to the immediacy of corrective actions: the shorter the feedback loop the better.

Source inspection checks for factors that cause defects. Immediate action corrects problems before a defect can occur. Defects are prevented by controlling their causal factors Because special causes can never be eliminated, only through 100% source inspection and immediate corrective action can zero defects be achieved.

Terminology

Process Capability = the ability of a process that is in statistical control to consistently meet customer requirements

Spaghetti Diagram

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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.

 

 

 

Business Case for Manufacturing Plan Verification

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An ounce of prevention is worth a pound of cure. Everyone knows and accepts this adage but in today’s lean global economy, not everyone has the people and the budget to walk the talk. Quantifying the answers to these questions will build the business case for manufacturing plan verification.

The Business Case for Manufacturing Plan Verification

(1) What is the value of minimizing the seven wastes (over-production, inventory, motion, over-processing, waiting, correction, and conveyance?
o operating costs
o investment

(2) What is the value of reducing the risk of capacity shortfalls found after a new production line or business process is launched?
o lost sales
o overtime
o overmanning
o post launch trouble shooting and additional investment

(3) What is the value of predicting operational and financial metrics prior to launching a new manufacturing or business process?
o direct / indirect labor utilization
o overall equipment effectiveness (OEE)
o dock-to-dock time
o work-in-process inventory
o finished product inventory
o build-to-schedule
o total contribution margin
o cash flow
o profits
o return on investment

(4) What is the value of verifying operating plans prior to launching a new manufacturing or business process?
o direct labor
o indirect labor
o shift hours
o quality control plans
o preventive maintenance plans
o mix / sequence flexibility
o batch sizes / changeovers
o scheduling and sequencing algorithms

(5) What is the value of actively managing the constraint during the planning of a new manufacturing or business process?
o flexibility
o expansion

The answers to these questions will likely roll up into a pretty big $$$ number. With today’s commercially available discrete event simulation software, the business case for manufacturing plan verification is therefore quite strong.

The world is full of uncertainty and change. Robust manufacturing plans will stack the odds in your favor. Simulate first to drive business plan targets down to each cell. Then simulate again to verify that the system works. An ounce of prevention is worth a pound of cure. In a nutshell, that is the business case for manufacturing plan verification.