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Find all articles across all article series listed in reverse chronological order.
It’s no secret that equipment maintenance software offers many benefits to your organization. However, organizations frequently find that the software doesn’t deliver the end results they anticipated. This often happens because organizations don’t maximize CMMS potential. In other words—they’re not using their software to its fullest potential.
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Effective execution is a matter of dealing with scarcity: a scarcity of time, a scarcity of resources, and scarcity of information (although too much information can also cause problems). Tools like a risk assessment help manage this scarcity by prioritizing things to allow you to better allocate resources on what’s most important.
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Maintenance and reliability maturity provides an understanding of both how well we do maintenance and how good is our maintenance program. One delivers a major business result, the other is a big part of how you get there. Doing maintenance with precision and care, so the job is done once and done well by the right people and without delay is what maintenance organizations strive for. Some achieve it, some struggle to do so. If they can achieve that, then they are being efficient.
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(This is chapter 5 of User Manual for Credible Reliability Prediction – Field Reliability (google.com), cleaned up and typeset for AccendoReliaiblity Weekly Update.)
The nonparametric maximum likelihood estimator for an M/G/∞ self-service time distribution function G(t) extends to nonstationary, time-dependent, Poisson arrival process M(t)/G/∞ systems, under a condition. A linearly increasing Poisson rate function satisfies the condition. The estimator of 1-G(t) is a reliability function estimate, from population ships and returns data required by generally accepted accounting principles.
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More companies are leveraging high speed vision systems to inspect multiple quality characteristics on their products.
For example, in a high volume baking operation, a vision system can test for bun height, bun length, slice thickness, topping distribution, surface color, and more. This happens automatically on the line at high speeds. In bottling or other plastic manufacturing, a vision system may inspect multiple dimensions and surface properties. [Read more…]
Cleaning is an important first step in Operator Care and reliability gains because:
Dirt in rotating parts, sliding parts, pneumatic and hydraulic systems, electrical and control systems, sensors, etc. causes malfunctions, reduce function, failure by wear, clogging, resistance, speed losses, etc. are different types of defects. Defects are anything that is abnormal from the expected ideal condition. Insufficient cleaning causes forced deterioration. All these losses are solved through a thorough cleaning of equipment and countermeasures to keep the equipment clean.
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Analysis of the Storm Packer (SP) failure in Article 1 will be complicated. Some stakeholders will assume that the SP was defective, some will assume the drilling crew made mistakes, and others will assume that wellbore conditions predisposed the SP to fail. Any of these may explain the failure of the first SP, but only rigorous due diligence will uncover the root cause(s). What should be investigated, and what will be the roadmap for the analysis? [Read more…]
Let’s start off with some honesty…the term ‘RCA’ (Root Cause Analysis) is quite vague, misleading and easily misinterpreted by those who are not immersed in its use. It is a useless and counter-productive term because there is no universally accepted, standard definition. Therefore, any process/tool someone is using to solve a problem is likely to be labelled as ‘RCA’. It could be troubleshooting, brainstorming and/or some other more structured problem solving approaches such as 5-Whys, fishbone diagrams, causal factor trees and/or logic trees.
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There is not a single maintenance department that I am aware of that has an unlimited budget. If you are aware of one, please let me know as I would love to see if it is successful or not.
Since most of us do not have an unlimited maintenance budget, we need to be smart about how we spend our maintenance money. Therefore there needs to be a balance and well thought out approach to the spend. We all know that proactive maintenance is cheaper than breakdown maintenance. But how do we balance the cost of maintenance with risk, to ensure that operations get the most out the equipment?
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Enterprise Risk Management (ERM) is a relatively new concept (been around 10-12 years). It is a top down approach to business system management and execution It is a risk-based problem solving and decision-making process. Everything is looked through a risk prism.
I suspect that many of the companies that have adopted ERM have not implemented it to the fullest extent of its capabilities. The reason is it takes a cultural change to do so and many companies do not know how to do it. This paper by example explains how to change the culture in a company to fully and completely implement ERM. [Read more…]
Asset Prioritization and criticality are used to provide a structured approach to determining the relative organizational risks and failure consequences associated with assets. This provides a means for the organization to focus on critical risks to the business.
An asset management system is comprised of all of the necessary processes, procedures, tools, systems, and methods necessary to meet business objectives in a manner which is controlled, measured, and improved upon. The system, more often than not, takes on some visual representation as in the graphic below. The purpose is to provide a simplified understanding of the overall process to meet asset management goals.
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In Part I of this article, we introduced the concept of utilizing Deviation from Nominal (DNOM) control charts for short production runs. These charts allow us to monitor process characteristics over time even when the units being controlled have varying nominal values. DNOM charts assume that the process variability (i.e. standard deviation) does not vary significantly by part type. However, often this assumption does not hold. Characteristics with larger nominal values tend to have more variation than characteristics with smaller nominal values. In Part II we discuss how to test whether or not significant differences in variability exist and if so, how to modify the DNOM methods and charts to handle this situation. [Read more…]
I got a call last week from a friend I used to work with who called just to catch up on what I had going on in life. After a few minutes of conversation on what each of us had going on he asked me what I thought of the phrase “Precision Maintenance.”
I must admit, I was a bit confused by the question. I told him I think a lack of precision maintenance might me the leading cause of failure for nearly every company in the world. I don’t think we spend nearly enough time training and certifying tradespeople in precision maintenance techniques and that the reduction in skilled trades apprentice programs has made the problem worse.
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Author’s Note: I want to reiterate that this Series about reading the basic fracture surfaces, is for novices who often come into contact with such failed components. This Series is about the basics (101), and is intended to give readers an appreciation for the value of such ‘broken’ parts to an effective investigation/RCA. While this information will be rudimentary to seasoned materials engineers/investigators, I know they will all appreciate heightening awareness to the need to retain such failed parts for formal analysis, versus throwing them away and just replacing the part. Throwing away failed parts is a recipe for a repeat failure. When one does not understand why the part failed in the first place, they can’t prevent it from failing again.
In this article we will focus on how to actually incorporate the evidence (failed parts) from a failure, into a disciplined Root Cause Analysis (RCA) process.