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Uptime Insights – 3 – Work Management

Uptime Insights – 3 – Work Management

Uptime Insights – 3 – Work Management

Reliability depends on the right maintenance being done the right way, and at the right times. At the core of making that happen is the work management process. It is a six step process that’s fairly simple, but often not followed very well.  Without, workforce deployment becomes reactive to emergencies and maintenance costs are high.  Work done in those reactive situations is anywhere from 1.5 to 3 times as expensive as work that is fully planned and executed on schedule.  In some industries the cost of emergency work is even higher.  [Read more…]

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How Should the Sample Size be Selected for an X-bar Chart? (Part II)

How Should the Sample Size be Selected for an X-bar Chart? (Part II)

An earlier article focused on the conceptual application of appropriate sample sizes for X-bar charts.  As we discussed, the purpose of control charts is to detect significant process changes when they occur.  When the proper sample size is selected, X-bar charts will detect process shifts (that have practical significance) in a timely manner. [Read more…]

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Understanding Plant Losses

Understanding Plant Losses

The Way Losses are Calculated
and OEE/TEEP Calculation

In order to get a broad, clear picture of where to focus, you have to view your whole plant as a large system of fully manageable processes. No matter your role, your job is to improve plant processes, helping to produce the highest quality product, at the lowest price possible, in the safest manner. In order to see this big picture, you have to be honest and expose true problems within your facility. From that perspective, you will be able to recognize the different types of losses in your plant and how to secure significant gains in productivity by controlling those losses.

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You’re Using the Wrong Average!

You’re Using the Wrong Average!

Imagine riding your motor scooter one sunny afternoon to your auntie’s home who lives near the sea, 20 miles from your home. On your trip there, the wind is at your back and the terrain slopes downward, resulting in an average speed of 25 mph. On the way home however, you’re motoring on a slight upward slope and into the wind, resulting in an average speed of 15 mph.

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‘Making’ and ‘checking’ reliability are very, very different

‘Making’ and ‘checking’ reliability are very, very different

At the 2019 Annual Reliability and Maintainability Symposium, I was involved in a discussion with US Department of Defense (DoD) reliability engineering teams and industry representatives. And on the agenda was a review of an emerging document called the ‘Reliability and Maintainability Engineering Management Body of Knowledge.’ Let’s call this the ‘DoD RAM BOK’ for short.

I only had access to this document’s quick reference guide, and it suggests that the DoD RAM BOK describes what reliability engineering activities need to happen from ‘concept’ through to ‘operations’ for a typical military capability being introduced into service. 

[Read more…]

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Collecting Failure Data: A Practical Approach

How to collect the failure data needed to drive improved plant performance.

The first step to any reliability improvement program is to define what data or information will be required to drive defect elimination.  In the previous posts, the following topics were discussed;

All of the topics discussed what data is required and how to structure the data to implement a reliability engineering program or defect elimination process.   Understanding the what, when and why set up and is required to setup a reliability engineering program.  However, where many organization fail in this process is getting the data collected in a consistent and timely manner. [Read more…]

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What is your Risk Appetite?

What is your Risk Appetite?

Guest Post by John Ayers (first posted on CERM ® RISK INSIGHTS – reposted here with permission)

Businesses take risks to pursue opportunities. What is your risk appetite? This question has been asked by companies for years. Risk appetite is the amount and type of risk an organization is able to support in the pursuit of business objectives. Examples of successful high risk appetite companies are: Amazon; Uber; and Tesla.

Risk appetite can be applied to your personal life as well especially today to thrive in changing times. Two stories of individuals with different risk appetite are presented below to illustrate how much you want to take can affect your life especially in retirement years. [Read more…]

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Planning for a DOE

Planning for a DOE

In this article post, we discuss the suggested steps for planning a Designed Experiment.

Step #1 – Clearly Define the Problem and Objectives

It is critical to clearly define the problem before beginning experimentation.  When the problem is not clearly defined and described, there will be confusion in designing and executing effective studies.  To define appropriate responses to measure requires that the problem be understood and agreed on.  Also, it is key to define the objectives of the actual experiment.  If the problem is to reduce scrap rate, how much of a reduction is targeted? [Read more…]

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Outsourcing or ‘Out of sight, out of mind?’

Outsourcing or ‘Out of sight, out of mind?’

I was having a lunch meeting with a project manager, and the topic of outsourcing came up. Specifically, outsourcing the manufacture of a particular machine that would form part of a larger vehicle system. I asked him why he was doing this, particularly when for many years the predecessor to this machine was very successfully manufactured in-house. His answer was simple.

It was to transfer risk to a supplier. [Read more…]

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Should You Worry About IoT If You Don’t Have the Basics Down?

What Good Is The Data If You Don’t Know What To Do With It?

As maintenance, reliability, and asset management professionals, we are in an amazing time.  We can collect virtually limitless amounts of data on the condition of our assets.  With this data, we can determine the exact condition of the assets, predict when the next failure is likely to occur and how it will occur.  Besides, with all of this data, we can move to prescriptive maintenance, where the maintenance actions are determined based on the asset condition, not a predetermined strategy.   I’ll touch more on prescriptive maintenance in next week’s post. [Read more…]