Your Reliability Engineering Professional Development Site
In the previous episode, the concepts of agile hardware product realization were introduced along with the idea of the ten best practices. Before diving into the details of these, there are a few basics to understand. In this episode Product Realization will be defined at a high level as well as the ideas behind a New Product Development Introduction (sometimes written as NPDI) framework.
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I generally write articles about topics I personally struggled to understand from the sources available to us, such as books, online resources, and so on. I believe most technical concepts are fairly straightforward at their core, but the way we express ideas and translate our understanding into writing often makes them harder for others to grasp. That is an area where we can all continue to improve.
As part of that journey, my goal with the Breaking Bad for Reliability newsletter is to be a communicator of Reliability Engineering principles, and I am doing this mainly for two categories of people:
This is a rather depressing title for an article specifically on the topic of Reliability. After all, Reliability relates to the Probability of Success hence the contradiction.
However, the contradiction is not so much one as Reliability Analysis depends on having access to failure data. In other words, if the equipment does not fail, it might be difficult or even impossible to perform an analysis. Of course, we can source other types of data that are not failure records, but this is not the common approach.
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How effective are the repair tasks you conduct on your equipment?
This article looks at quantifying the effectiveness of corrective maintenance, typically an unplanned repair on an asset. Unplanned repairs are undesirable because the asset loses its function and cannot produce what is required often leading to loss of revenue. Yet, this advent is inevitable because assets are subject to degradation over time.
The effectiveness of a repair relates to the condition in which the asset is restored to after a repair. But also how long it will operate until the next repair, Evaluating the effectiveness of the repair will provide the asset operator with a decision making tool. Can we do something different if the repair effectiveness is unsatisfactory? Or do we have to replace the asset as it is failing too frequently?
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Ernst Hjalmar Waloddi Weibull (18 June 1887 – 12 October 1979) was a Swedish engineer, scientist, and mathematician. (source Wikipedia)
The history of Design of Experiments (D.O.E) can be traced back to the work of various individuals, including Genichi Taguchi, a Japanese engineer and statistician. Taguchi made significant contributions to the field, particularly in the area of robust design, which aimed to improve the quality of products and processes. His work was influenced by the need for quality improvement in post-World War II Japan. Taguchi’s methodology, known as the Taguchi methods, was based on the concept of “robust parameter design,” which aimed to make processes and products insensitive to environmental factors or other variables that were difficult to control.
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This is our first video on ALT in a series of videos on this important topic in reliability engineering. In this video, Hemant Urdhwareshe has introduced basic concepts of ALT. In our subsequent videos on ALT, we will do a more detailed discussion on mathematical treatment, selection of appropriate model and statistical distribution. We will explain these with application example on Minitab software. Hemant is a Fellow of ASQ and is ASQ CRE, CMBB, CSSBB, CQE and CMQ/OE. We are sure that viewers will find it useful.
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Have you ever tried to implement any asset improvement activity but it didn’t go so well? Couldn’t rally the troops? Couldn’t get the kind of management buy-in that you really needed to get things off the ground? If so, you’re not alone.
I’ve read too many articles describing that up to 70% of asset improvement initiatives fail. And I think it’s because a lot of people don’t have a basic understanding of maintenance and reliability principles. So they don’t understand why “change” needs to take place.
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And again there is no one answer for such simple question. Strongly depends on what type of test you need to conduct.
It is also very important to understand at which stage, design of the product. Usually at very early stages of the design there is many unexpected failures, when design is mature enough – failures become predictable, and there is one last period, called – wear out/aging stage.
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Focus on failure elimination, otherwise equipment failures never stop because they are forever being introduced and perpetuated by poor procedures and practices, poor quality control and poor business management systems.
Knowing defects cause future equipment failures, production downtime, unnecessary costs and lost profits, it is necessary to put defect elimination strategies into place to purposely stop defects occurring and to remove the defects that are already present.
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We are happy to release this video on Lognormal Distribution which is a popular distribution to model failures of non-repairable items. In this video, Hemant Urdhwareshe has explained basic concepts of lognormal distribution and its application examples. Hemant also explains its mathematical relationships to calculate MTTF, standard deviation and other parameters In addition, in the video, Hemant has illustrated how to use Minitab and Excel to visualise Lognormal Distribution. Hemant is a Fellow of ASQ and is ASQ CRE, CMBB, CSSBB, CQE and CMQ/OE. We are sure that viewers will find it useful.
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Plant and equipment failures are business process failures. Plant stoppages and breakdowns result from failure-causing practices built into business processes and from leaving the right reliability practices out of them. Processes may superficially look okay because they have documentation, charts and records, but if you suffer a steady stream of failures, problems, and rework, then your processes contain unforeseen ‘traps’ into which your people and equipment regularly fall. Failure was not intended when your processes were chosen and designed, but failure is what happens when they are used.
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In this video, Hemant Urdhwareshe explains how to estimate tolerance interval at given confidence level and specified percentage of distribution. The purpose of tolerance intervals is to assure that the tolerance limits specified during design are achievable during production! Often, the designers specify tolerance limits that are not demonstrated and create lot of rework and/or rejection during production phase. This can increase cost of poor quality (COPQ) and result in redesign of the product and/or revising specifications after the product is released for production. Changes made after product launch can be expensive
I am adding a small correction: at 7:01 minute, please read the tolerance interval as 152 to 308, (and not 358 as shown in the footer).
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Air, sea, space, land, or underground? Commercial, government, or military? Reliability Centered Maintenance has something for everyone!
Absolutely. In fact, in Stanley Nowlan and Howard Heap’s book on RCM, they state:
The content of scheduled-maintenance programs developed by experienced practitioners of MSG-2 techniques may be quite similar to the programs resulting from RCM analysis, but the RCM approach is more rigorous, and there should be much more confidence in its outcome. The RCM technique can also be learned more quickly and is more readily applicable to complex equipment other than transport aircraft.
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Companies that want plant and equipment reliability need to engage the people in the workplace and give them a large degree of responsibility for improving the performance of their equipment. The most successful solution yet discovered to do that is the autonomous work team.
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