Use Periods Of Low Production Output To Improve Process Reliability And Consistency


The world business cycle took a severe downward turn in the 4th quarter of 2008.  Evidence points to a world-wide depression necessitating lower production output.  Cloudy crystal ball predictions infer the depressed output may extend for 4 to 8 years. 


Production orders are being cancelled.  Normally sold-out processes are being shut down or operating with severe cutbacks in production output.  These cutbacks are special cause events outside of the boundary of plant control, and now we need to make major improvements in control of common cause variability to survive with lower costs.

What do cutbacks in production portend?

Historically, during production retrenchment periods, production output variability increases from common cause attributes.  The increased scatter in output occurs because industrial discipline is lost during the forced retreat from high output to lower output.  Now is an ideal time to institute increased industrial discipline for cost reduction purposes and to set the stage for better results when the upturn occurs to:

1)      achieve reduced output with reduced variability in production output,

2)      produce lower output with proportionally fewer resources for a major cost reduction opportunity,

3)      use the low output time period to function as a laboratory in a search for finding old abuses and permanently removing non-productive practices, and

4)      insist on production performance to a new and less costly production scheme.

If you can’t find the problems during low output periods and correct them now, expect more atrocities will creep into a deteriorating production system. This will incorporate further bad habits when high production levels are required in the future and then you can’t achieve the former good results at higher output. 


Now is the time for implementing strong corrective action! 

You can not maintain the status quo in production.  Production systems either get worse or get better.  You must input strong energy to overcome the normal entropy rush toward chaos.  Make positive changes now for improvements.  If you can’t make the improvements in a small output environment, you’ll never make the changes when the mass of the production organization increases!  If you miss this improvement opportunity in the lean years, you must worry!  Why?  Your leaner and hungrier improvement minded competitors will put you out of business.  It’s a simple business relationship: you either rise or fall.  Study your processes.  Find the faults.  Correct the faults now—don’t wait.


Industrial discipline-

In prosperous times, when production orders are generous, most production processes are littered with many small abuses accumulated from lack of industrial discipline.  Discipline in industry is defined as:

            1.   to train,

2.   to direct,

3.   to mold,

4.   to control, and only as a last resort does it mean;

5.   to punish. 

These items are management responsibilities and prerogatives [As the production leader, it is management’s prerogative to display leadership and correct loss of industrial discipline which crept into the organization during heavy production years]. 


Each item noted above is frequently involved in the seven deadly sins of supervision.  Deterioration in any of the five items will introduce greater variability in production quantity, production quality, production cost, and production delivery control.


An example of discipline is frequently demonstrated in military marching formations where the military can march in lockstep with precision. 


Contrast good discipline with the poor discipline of Keystone Cops.  Wikipedia defines Keystone Cops as an example “used to criticize any group for its mistakes, particularly if the mistakes happened after a great deal of [wasted] energy and activity, or if there was a lack of coordination among the members of the group”—see a You Tube Keystone Cops visual example for an illustration.  In an industrial environment, Keystone Cops practices will produce two measurable results by use of Weibull process reliability plots which identify special cause and common cause variations.


The process discipline goal for improvements is simple to explain (not easy to do!).   Industrial discipline must be integrated and aligned into the objective for these improvements:

1.      near perfect consistency in daily production output using process discipline for predictability,

2.      near perfect use of minimum resources for production for adding company value,

3.      near perfect consistency in low production costs for competitive advantage,

4.      near perfect consistency in production quality for meeting customer objectives,

5.      near perfect consistency in fast product deliveries for meeting customer objectives,

6.      near perfect flexibility and agility in response to customer needs (considering assets available for use) for a willing partnership with customers,

7.      near perfect utilization of human asset teamwork by empowerment and enablement of the entire organization.

These attributes are similar to principles of Lean Six Sigma and the book Process Discipline by Bennett and Edelson.


What’s the motivation for achieving these difficult improvements?

1.      consistency in daily output à produce a constant monthly paycheck for the

2.      consistent use of minimum resources à avoid waste,

3.      consistently achieve low production cost à survival of the fittest,

4.      consistently maintain quality à retain existing customers (and their orders),

5.      consistently produce fast deliveries à predictability with fast deliveries
avoids loss of customers (and their orders),

6.      demonstrate flexible and agility in customer response à build stronger
partnerships with customers,

7.      motivate human asset teamwork à build better links with humans for
better problem solving abilities.

Of course you can truthfully argue these motivations exist during times of plentiful orders or sparse order.  During sparse times you need the extra effort to cover and dilute the fixed cost of the business to achieve profitability.


Industrial discipline abuses are manifest with two measurable key performance indices (KPIs) when daily production output is plotted on a Weibull production plot.  The daily Weibull production plots will show these two KPI abuses:

1.      Flat line slopes (small Weibull beta values which define line slope) indicating
excessive scatter in daily output.

2.      Few data points with consistently high output (low reliability which is obvious
as a cusp on the Weibull plot).

Desirable processes will have two key items that can be measured:

1.      Steep Weibull betas (small variability in output), and

2.      High reliability (consistently high output) before evidence of a cusp on the
Weibull plot.

Management controls these industrial discipline issues with management prerogatives.  Control industrial disciple else you incur losses due to a hidden factory.  The hidden factory is also quantified by a Barringer Weibull process plot. 


It is easier to manage operations at lower output when fewer people are involved.  You can see abuses that have crept into the smaller operations.  Smaller operation can not hide scrap, wasted time, delays, and other hidden factory losses.  Removed hidden factory losses from the production process to avoid waste.  Use the reduce output periods to become more 1) efficient, 2) productive, and 3) predictable.  Become more predictable during low production periods which  will rotate the Weibull production line to become steeper.  Then when production increases, you simply translate the improved and steeper production line to the right on a Weibull plot which is toward higher output.


In summary.

A European colleague working on process reliability problems summarized the issues this way:

1.    “In bad times you need good management that controls and improves the process.  The aim is to deliver better customer value with less effort.  Saying that better control is unimportant in bad times is bad management—this poor management attitude is one root of the production process crisis.  The mechanism to control your process is to achieve high Weibull betas for consistent output, achieve high reliability for greater predictability, and during the period of low demand the demonstrated eta values are low on purpose from a special cause.  Then when demand returns the keys are in place for higher profitability.

2.    Ben Bernanke’s diagnosis of the 2008-2009 fiscal problems in the USA he said “We have a total loss of control”—can you imagine that Bernanke would continue the assessment with the phrase “but it doesn’t matter”!”


Barringer Weibull process reliability plots are NOT about the statistics.  Barringer Weibull process reliability plots ARE about quantifying and selling an improvement program for achieving more productive plants.  The Weibull plots show you the types of problems and quantify them.  You must ferret out the problems one-by-one and you must fix them to improve profitability.  This means you must make a corrective change to get an improvement change.  Remember, inaction will not preserve your job in financially difficult times.


The Weibull plots provide indices which you can benchmark for management action regarding Weibull slopes, beta.             

1.      Processes with beta slopes of 3-20 are in big trouble.  Small slope values describe too much output variability.

2.      Processes with beta slopes of 75 to 100 are superior processes.  Steep slopes describe small output variability. 

3.      You need consistent output with steep slopes in good times and bad times for better profitability.

4.      Your Weibull beta line slopes do matter!  They need to be steep.   Steep Weibull lines reduce efficiency and utilization losses which is part of your hidden factory!

5.      Use the bad times of the recession to get control over your output.  You need survival today.  You need competitive advantage in 2010+.

Reliabilities demonstrate consistent production results at high output levels are important indicators. 

1.      Processes with reliabilities of 10%-30% are in big trouble. 

2.      Processes with reliabilities of 80% are superior results

3.      It does matter what your process reliabilities are.  Low reliability drives special cause losses!

However, if you’ve got excellent reliabilities on a line slope of 3-20, you in a position of feeling proud about have the deck chairs aligned evenly on the Titanic as you sink—it’s a futile effort.

1.      The Weibull process reliability issue is not about playing the Enron game of using indices for self-enrichment and manipulation of the numbers.  Barringer process Weibull plots are about using the indices to improve profitability for the company by reducing losses.

2.      Production processes require a learning organization to make improvements.

3.      Lack of production process improvements indicates lack of a forward thinking management team.  Perhaps you’ve got to make a change in
management to get the profitability change you need for the business.  Management must lead for improvements or get out of the way as times in 2009 are tough.  Survival today is important, but long term survival of the business by way of improvements is essential for business survival.


Other process reliability articles to read:

·         Special Cause Variations, Common Cause Variations, and Process Reliability Plots   

·         Summary Of Process Reliability 

·         Process Reliability Punch List

·         Production Output/Problems

·         Six Sigma

·         Coefficient of Variation

·         Production Reliability Example With Nameplate Ratings

·         Key Performance Indicators From Weibull Production Plots

·         Production Nameplate Rating

·         Process Reliability Plots With Flat Line Slopes

·         Process Reliability Line Segments

·         Automating Monthly Weibull Production Plots From Excel Spreadsheets      
    Papers On Process Reliability As PDF Files For Downloads
      - New Reliability Tool for the Millennium: Weibull Analysis of Production Data
      - Process Reliability and Six-Sigma
      - Process Reliability Concepts

You can download a PDF file copy of this page .

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March 8, 2010
© Barringer & Associates, Inc., 2009