Using A3: Toyota’s Process Improvement Tool

A3 report, Toyota A3, problem solving A3

Q: I’m interested in obtaining more information about A3, a process improvement tool created by Toyota.  Do you have any resources that explain the ways to use A3 or offer a template?

A: Thank you for contacting ASQ.  The Learn About Quality portion of ASQ’s website hosts a helpful A3 Report page, which will certainly be helpful to you.

For more information on this topic, visit ASQ’s website.

ASQ’s Research Librarian

Modifying Programmable Logic Controllers (PLCs)

PLCs, programmable logic controllers

Q: I am seeking a standard to monitor, control and communicate existing Programmable Logic Controller (PLC) program changes.

We have a team of 15 electricians. They have access to various machinery and their PLCs. They can make modifications to majority of PLC programs.

The changes are under communicated and the current process in not monitored. We do capture log in/log out and some changes, but this is not sufficient.

Bud Salsbury’s take:

A: If these are Ethernet IP equipped PLCs that support remote login and can be network attached at all times, it isn’t an issue. It becomes an IT admin thing. For example, Allen Bradley’s PLCs can have their programs placed out on the network and treated like an FTP site. The PLCs can pull their programs at each start up from their predefined folders.

If we are talking about standalone PLCs, with no network,  it becomes a whole different animal. It is then more of a procedural thing. You must again place the master copy of the program on a network location, but it is up to each programmer to follow a routine, pull the program from the network, update, upload to the PLC, test/verify, and if good–replace the master copy. Now, if any step is missed, you’re up that well known waterway without any visible means of locomotion.

Ethernet IP is your friend. Note: they have to be newer/smarter PLCs to play nice.

Now if you are making changes to the program (whether it is a robot, or an NC machine, or a molding press), then these changes would probably affect the overall production process. Also, if the changes could affect the quality of the product in any way (either good or bad), then, at the very least, there should be a type of “deviation” procedure where the quality level of the product is verified after the process deviation has been implemented and prior to releasing any new parts produced off of this deviated process.  Also, there should be record of the before and after settings.

Bud Salsbury
ASQ Senior Member, CQT, CQI

Thea Dunmire’s take:

A: There are a number of significant risks associated with making modifications to PLCs used to control industrial equipment.  When you are modifying PLCs, you are making changes to “the brains” of your operations.  These changes can result in equipment that does not function properly, production lines that completely shut down or critical infrastructure that stops operating (e.g. water pumping stations that stop working). Thousands, or even millions, of dollars can be lost because of the modification or malfunction of a single PLC. These malfunctions can be caused by lack of ongoing maintenance, ill-conceived “trial-and-error” modifications, or even the insertion of malicious code by external hackers or disgruntled employees.

Organizations should have control processes in place that address all PLC modifications. Control processes are clearly required for PLCs that are used for safety-related applications or high-hazard process operations. For organizations that are certified to OHSAS 18001:2007 Occupational health and safety management systems — Requirements, management-of-change procedures must be established to assess the potential hazards of PLC modifications prior to any changes being made. After the fact validation is not acceptable.

There are a number of potentially applicable regulations and standards – whether they are actually applicable to your operations depends on the nature of the processes and equipment being controlled. It is important for organizations to carefully assess which requirements need to be met and institute the processes needed for conformance. In addition, organizations should periodically evaluate the robustness of the established systems to ensure the ongoing integrity of all PLC controlled operations.

Examples of potentially applicable regulations and standards include:

  • IEC 61508 Functional safety of electrical/electronic/programmable electronic safety-related systems defines the requirements for programmable electronic systems used in the safety-related parts of controls systems.
  •  U.S. regulations, including 29 CFR 1910.147 (Lockout/tagout requirements), 29 CFR 1910.119 (OSHA Process Safety) and 40 CFR 68 (EPA Risk Management Plan)
  • NFPA 79 – Electrical Standard for Industrial Machinery
  • ANSI B11.1 and EN 692 – safety requirements standards for mechanical presses
  • ANSI/RIA 15.06 – standard for industrial robots and robot systems

This is a complex area that requires input from individuals with specific training and competence in working with PLC controlled equipment.  It is not an area to for improvisation – the risks are too high.

Thea Dunmire, JD, CIH, CSP
Chair, ASC Z1-Audit Subcommittee
ENLAR Compliance Services, Inc.
Largo, FL
http://www.enlar.com

For more on this topic, please visit ASQ’s website.

Difference Between ISO/IEC 17025 and ISO 10012

ISO/IEC 17025:2017 General requirements for the competence of testing and calibration laboratoriesQ: I am updating the instrumentation section of a product fabrication specification to replace a cancelled military specification (MIL-STD 45662) that specified calibration systems requirements.  I am looking for an industry standard that provides requirements/guidance for documentation of our established schedules and procedures for all of our measuring and test equipment and measurement standards.

I am looking into ANSI/ISO/ASQ Q10012-2003: Measurement management systems — Requirements for measurement processes and measuring equipment and ISO/IEC 17025-2005: General requirements for the competence of testing and calibration laboratories, and I would like guidance on usage and application of these standards.

A: The two standards in question, ISO 10012 and ISO 17025 have different scopes.

While the scope of both documents includes language that can perhaps cause confusion, what follows is the salient text from both that illuminates the difference between the two.

From the scope of ISO 10012:

“It specifies the quality management requirements of a measurement management system that can be used by an organization performing measurements as part of the overall management system, and to ensure metrological requirements are met.”

From scope of ISO 17025:

“This International Standard is for use by laboratories in developing their management system for quality, administrative and technical operations.”

ISO 10012 focuses on the requirements of the measurement management system. You can consider it a system within the quality management system. It defines requirements relevant to the measurement management system in language that may illustrate interrelations to other parts of an overall quality management system.

ISO 10012 is a guidance document and not intended for certification. An organization, for example, could have a quality management systems that is certified to ISO 9001:2008. Even if the organization chooses to adhere to the requirements of ISO 10012, the certification to ISO 9001 does not imply certification to the requirements of ISO 10012.

ISO 17025 describes the requirements for a quality management system that can be accredited (a process comparable but different from certification). It encompasses all aspects of the laboratory.

The competence referred to in the title of the standard relates to the competence of the entire system – not just training of personnel. It addresses such factors as contracts with customers, purchasing, internal auditing, and management review of the entire quality management system – ISO 10012 does not.

In summary, ISO 10012 is a guidance document that addresses one element (namely management of a measurement system) of a quality management system. ISO 17025 defines requirements for entire quality management system that can be accredited.

Denise Robitaille
Vice Chair, U.S. TAG to ISO/TC 176 on Quality Management and Assurance
SC3 Expert – Supporting Technologies

Related Content:

Expert Answers: Metrology Program 101, Quality Progress

Measure for Measure: First Step Toward Disaster, Quality Progress

10 Quality Basics, Quality Progress

Standards Column: Using the Whole ISO 9000 Family of Quality Management System Standards, Quality Engineering

Root Cause Analysis Samples

Q: I am looking for samples of a RCA.  I will be doing training on that topic and I would like to have some samples to use with the participants.

A: Thank you for contacting ASQ and the Quality Information Center.  I received your request for samples of root cause analysis.  Root cause analysis is defined as a “quality tool used to distinguish the source of defects or problems.  It is a structured approach that focuses on the decisive or original cause of a problem or condition” (from The Quality Improvement Glossary by Donald L. Siebels).

Root cause analysis figure

The image (right) is take from Root Cause Analysis: Simplified Tools and Techniques.

I found hundreds of RCA results on ASQ’s website (if you wish to browse through them all, here is the link to my original search results).  I thought you might be most interested in case studies which provide examples of how root cause analysis has been used.  I found more than 100 case studies which focus on root cause analysis and I’ve listed some case studies below which I thought would be helpful:

Abstract: Customer Complain investigations weren’t getting to root causes.  Logic trees proved more effective than fault trees in determining what actually went wrong.  After root cause analysis, complaint numbers dropped by half.  That and indirect benefits led to bottom-line results.

Abstract: The authors used Six Sigma to improve the process of manufacturing gear boxes for mechanical power transmission at a foundry in India. The goal was to improve product performance by reducing variation in the casting of components, thereby reducing defects. The analyze phase used root cause analysis and failure mode and effect analysis to identify several process variables, including pattern design and maintenance, worker training, and the proportions of scrap and coal inputted into the molds, that were increasing the frequency of the major defects.

Abstract: A root cause analysis project saved Clipper Windpower $1 million in lost revenue. By identifying the root causes of turbine failure during inclement weather, Clipper increased customer satisfaction through improved turbine availability. This project also supported a key supplier’s quality process, as Clipper’s team helped redesign and test an improved anemometer. Team members mastered quality tools and strategies, preparing them for future improvement projects.

Abstract: Cross-functional teams identified root causes of injuries and reduced accidents by 48 percent in one year while saving an estimated $714,000 in cost avoidance over a 24-month period. To compile data and identify root causes, team members used trend graphs, Pareto diagrams, bar charts, and fishbone diagrams. A key tool used in developing an action plan was the solution selection matrix, a systematic approach that allows for the best possible solutions to surface.

The following webcasts may also be helpful for those who are new to root cause analysis:

Root Cause Analysis for Beginners, Part 1” & “Root Cause Analysis for Beginners, Part 2

I hope that this information is helpful.  Please feel free to contact me with any questions or if you need additional assistance.

Best regards,

ASQ Research Librarian
Milwaukee, WI

Gage R&R Study on a Torque Wrench

Gage R&R, Torque Wrence

Q: I need information on performing a Gage R&R on a torque wrench. We are using the wrench to check customer parts.

A: For reference on both variable and attribute Gage R & R techniques, a good source is the Automotive Industry Action Group (AIAG) Measurement Systems Analysis (MSA) publication.

The traditional torque wrench is a “generate” device in the sense that it generates a torque to tighten or loosen a fastener (a nut or a bolt, etc.). So, in a strict sense, it is not a “measurement” device. Therefore, both preset and settable torque wrenches are set to a torque value and then used to tighten a fastener or loosen a fastener. When loosening a fastener, it will determine how much torque is required to loosen the fastener. Usually, the clockwise motion is for tightening and counterclockwise motion is for loosening in a torque wrench.

To conduct a variable Gage R & R study on a torque wrench, we would need a “measurement” device which would be a torque checker with a capability to register peak (or breaking) torque. Many such devices are commercially available and if a facility is using torque wrenches, it is a good idea to have one of these to verify performance of torque wrenches. Such a device is usually calibrated (ensure traceable accredited calibration) and provides reference for proper working of torque wrenches.

Now,  one would conduct a Gage R&R study using the typical format:

  • Two  or more appraisers.
  • 5 to 10 repeat  measurements at a preset torque by each appraiser, replicated 2 to 3 or more times.

A word of caution on torque wrenches and setting up the Gage R&R:

  • The measurement is operator dependent, so operators need to be trained on proper toque wrench usage techniques.
  • Ensure that torque is set between every measurement in the settable torque wrench to simulate actual usage between repeated readings.
  • Ensure the number of repeated reading and replicated readings are the same for all appraisers.

The templates for data collection are available in spreadsheet format  from commercial providers. Alternatively, one can design the template from the MSA publication referenced. The data would be analyzed using the guidelines from the MSA publication.

Good luck with the Gage R&R! It is a very useful and worthwhile exercise in understanding your measurement process.

Dilip A Shah
ASQ CQE, CQA, CCT
President, E = mc3 Solutions
Chair, ASQ Measurement Quality Division (2012-2013)
Secretary and Member of the A2LA Board of Directors (2006-2014)
Medina, Ohio
http://www.emc3solutions.com/

Related Content:

To learn more about this topic, visit ASQ’s website.

AQL for Electricity Meter Testing

Chart, graph, sampling, plan, calculation, z1.4

Q: We have implemented a program to test electricity meters that are already in use. This would target approximately 28,000 electricity meters that have been in operation for more than 15 years. Under this program, we plan to test a sample of meters and come to a conclusion about the whole batch  —  whether replacement is required or not. As per ANSI/ISO/ASQ 2859-1:1999: Sampling procedures for inspection by attributes — Part 1: Sampling schemes indexed by acceptance quality limit (AQL) for lot-by-lot inspection, we have selected a sample of 315 to be in line with the total number of electricity meters in the batch.

Please advice us on how to select an appropriate acceptable quality level (AQL) value to accurately reflect the requirement of our survey and come in to a decision on whether the whole batch to be rejected and replaced. Thank you.

A: One of the least liked phrases uttered by statisticians is “it depends.” Unfortunately, in response to your question, the selection of the AQL depends on a number of factors and considerations.

If one didn’t have to sample from a population to make a decision, meaning we could perform 100% inspection accurately and economically, we wouldn’t need to set an AQL. Likewise, if we were not able to test any units from the population at all, we wouldn’t need the AQL. It’s the sampling and associated uncertainty that it provides that requires some thought in setting an AQL value.

As you may notice, the lower the AQL the more samples are required. Think of it as reflecting the size of a needle. A very large needle (say, the size of a telephone pole) is very easy to find in a haystack. An ordinary needle is proverbially impossible to find. If you desire to determine if all the units are faulty or not (100% would fail the testing if the hypothesis is true), that would be a large needle and only one sample would be necessary. If, on the other hand, you wanted to find if only one unit of the entire population is faulty, that would be a relatively small needle and 100% sampling may be required, as the testing has the possibility of finding all are good except for the very last unit tested in the population.

AQL is not the needle or, in your case, the proportion of faulty fielded units. It is the average quality level which is related to the proportion of bad units. The AQL is fixed by the probability of a random sample being drawn from a population with an unknown actual failure rate of the AQL (say 0.5%), creating a sample that has a sample failure rate of 0.5% or less. We set the probability of acceptance relatively high, often 95%. This means if the population is actually mostly as good as or better than our AQL, we have a 95% chance of pulling a sample that will result in accepting the batch as being good.

The probability of acceptance is built into the sampling plan. Drafting an operating characteristic curve of your sampling plan is helpful in understanding the relationship between AQL, probability of acceptance, and other sampling related values.

Now back to the comment of “it depends.” The AQL is the statement that basically says the population is good enough – an acceptable low failure rate. For an electrical meter, the number of out of specification may be defined by contract or agreement with the utility or regulatory body. As an end customer, I would enjoy a meter that under reports my electricity use as I would pay for less than I received. The utility company would not enjoy this situation, as it provides their service at a discount. And you can imagine the reverse situation and consequences. Some calculations and assumptions would permit you to determine the cost to the consumers or to the utility for various proportions of units out of specification, either over or under reporting. Balance the cost of testing to the cost to meter errors and you can find a reasonable sampling plan.

Besides the regulatory or contract requirements for acceptable percent defective, or the balance between costs, you should also consider the legal and publicity ramifications. If you accept 0.5% as the AQL, and there are one million end customers, that is 5,000 customers with possibly faulty meters. What is the cost of bad publicity or legal action? While not likely if the total number of faulty units is small, there does exist the possibility of a very expensive consequence.

Another consideration is the measurement error of the testing of the sampled units. If the measurement is not perfect, which is a reasonable assumption in most cases, then the results of the testing may have some finite possibilities to not represent the actual performance of the units. If the testing itself has repeatability and reproducibility issues, then setting a lower AQL may help to provide a margin to guard from this uncertainty. A good test (accurate, repeatable, reproducible, etc.) should have less of an effect on the AQL setting.

In summary, if the decision based on the sample results is important (major expensive recall, safety or loss of account, for example), then use a relatively lower AQL. If the test result is for an information gathering purpose which is not used for any major decisions, then setting a relatively higher AQL is fine.

If my meter is in the population under consideration, I am not sure I want my meter evaluated. There are three outcomes:

  • The meter is fine and in specification, which is to be expected and nothing changes.
  • The meter is overcharging me and is replaced with a new meter and my utility bill is reduced going forward. I may then pursue the return of past overcharging if the amount is worth the effort.
  • The meter is undercharging me, in which case I wouldn’t want the meter changed nor the back charging bill from the utility (which I doubt they would do unless they found evidence of tampering).

As an engineer and good customer, I would want to be sure my meter is accurate, of course.

Fred Schenkelberg
Voting member of U.S. TAG to ISO/TC 56
Voting member of U.S. TAG to ISO/TC 69
Reliability Engineering and Management Consultant
FMS Reliability
http://www.fmsreliability.com

For more on this topic, please visit ASQ’s website