Equipment Downtime Reports: The Data Your Mobile Workers Should Collect and Analyze

August 7, 2018

As a Plant Operations Manager, it’s your job to make sure your your production contracts are delivered on time and up to quota. That means making sure your plant’s equipment performs to scheduled capacity. Any time equipment goes down unexpectedly, your plant is on the hook for lost production time, repair costs, and possibly contractual penalties for late delivery. Downtime cuts into profits, and too much of it can result in losses for a quarter, or a year.

Minimizing downtime is clearly key to keeping operating costs in check and increasing profit. The best way to reduce downtime on your plant’s equipment is to understand how that equipment works, why it fails, and what indicators can best predict pending failure. To learn this information about your specific assets, you’ll need to collect baseline data, and specific equipment downtime reports, which you’ll analyze to develop strategies to prevent unexpected equipment failure.

Two types of data will help decipher the when and why of your equipment failure: failure data, and baseline data. Failure data are the circumstances and results of each instance of equipment malfunction. Baseline data are continuous diagnostic information from your equipment under normal and abnormal operating conditions. Collecting both sets of data allows you to compare them against each other, which can identify or isolate important trends and anomalies.

 

Collecting Failure Data as Equipment Downtime Reports

While the specific details you’ll need to collect on your equipment when failure occurs vary beyond simple description, certain categories of information provide a solid framework for understanding the causes of malfunction. Interpret the categories using your own knowledge of the workings of your plant. Failure data, compiled as Equipment Downtime reports, should include: 

    • Time of failure. Knowing the time of failure is essential for comparison to current and historical baseline failure, as well as for contributing to an ongoing historical record.
    • Nature of the failure. The specific details of the failure. Where did it start? Did a single component fail? Did a cascading reaction occur? Were multiple internal systems affected?
    • Cause of failure. Determine whether the failure was caused by operator error, process error, maintenance error, normal wear and tear, or external events. The cause of failure may be complex, a combination of multiple factors.
    • Cost of failure. Include length of downtime, cost of labor, cost of repair parts, and any resulting costs incurred by missed deadlines, fixed payments made during non-productive periods, and workman’s compensation

Failure data should be collected promptly when an incident occurs, before memories fade and fresh priorities claim precedence. The data must be visible and capable of informing action as well, to justify the cost of its collection. As such, it should be input and labeled—with as few steps as possible—into your plant’s Historian or computerized maintenance management system (CMMS). There, it can be reviewed, compared with other reports, automatically trigger work orders, and analyzed en masse to inform your future actions.


Collecting Baseline Data on Normal Equipment Operations

When possible, scientists include a control group in their experiments. While they alter conditions in other groups, they make no alterations to the control group. Then, when they collect the data from all their trials, they have a baseline for comparison. Same thing at your plant: With baseline data on normal operating conditions, you’ll be able to understand exactly how abnormalities differs from normal operations. By looking closely at historical baseline data preceding known events, you may also identify indicators that a failure was going to occur.

Knowing what signs indicate oncoming failure, you’ll be able to act proactively to prevent equipment failure the next time you see those indicators. Keeping a constant eye on your equipment’s information output lets you react immediately to any noticeable variation in your equipment’s operation.

Like failure data, the specific baseline data relevant to your equipment will vary. Baseline data can likewise be grouped into categories. An additional layer of categorization can be added to baseline data, since it is data is collected in real-time. Baseline data can be divided into data which is collected by automatic sensors attached to equipment, and data which must be recorded by mobile operators making rounds.

Automatic Collection of Baseline Equipment Data

Much, but not all, quantifiable data on your equipment’s continuous operations can be collected by automatic sensors. Automatic sensors are particularly effective in highly instrumented facilities, where they can be easily synchronized to a distributed control system (DCS). Certain equipment conditions, such as noise, leaks, physical damage are not easily sensed using instrumentation, and still must be observed using human senses.

Data which automatic sensors can detect includes:

  • Component temperatures
  • Lubrication temperatures and levels
  • Liquid and gas levels
  • Flow-rate of liquids and gases
  • PSI of liquids and gases
  • RPMs
  • Fuel consumption
  • Power consumption

Even highly instrumented facilities, however, still have equipment that has gauges, level indicators and other variable indicators that are not tied into a control system. These variables as well as equipment condition reporting that require human senses to observe need to be monitored by Mobile Operators on regularly scheduled Operator Rounds.

Operator Collection of Baseline Equipment Data

Nothing beats eyes in the field and boots on the ground. Your Mobile Operators collect valuable qualitative data about your equipment continuously. Where  automatic sensors are not used, they collect quantitative data as well. Automatic sensors are great at constantly monitoring narrow streams of information. Mobile Operators are great at monitoring everything else.

Often, obvious data which can lead to failure is undetectable by automatic sensors. Sensory data, like leaks, screeching or jangled noises, or unusual smells are all glaring indicators of pending equipment failure that may not be picked up by automatic sensors. Some of the essential information which Mobile Operators collect includes:

  • Visual Data. Rust, mold, rot, cracks, tears, dents, bad welds, excess or unexpected smoke, loose fasteners or indications of pest damage, etc. Visual information also includes readings taken from dials, meters, or sight glasses.
  • Auditory Data. Changes in pitch or tone of usual operating noises, screeching, straining, hissing, crackling, sudden reports or detonations, anything unusual.
  • Olfactory Data. The smell of smoke or fire, sulfur, other unusual chemical odors
  • Tactile Information. Excessive or unusual vibrations in the ground or equipment. Unexpected heat or cold.

    Collecting Baseline and Failure Information for Analysis

    In order for this baseline information to be useful and to justify its collection, it must be compared to the information collected in your equipment downtime reports. Therefore, it should likewise be entered into your CMMS, in as efficient a manner as possible.

    Since you are using the information to detect future failures as well as to understand past failures, the sooner you’re able to enter the information in your system, the better. After all, you can’t detect a pending failure until you see the data. During any lag time between collection and data entry, your equipment could be developing a costly issue.

    Automatic sensors can be configured to stream relevant data directly into your CMMS. Your Mobile Operators will need to record their data, either on paper or in an app, then transfer that data to your CMMS. If you have mobile asset reporting software, you may be able to eliminate redundant data entry by synching your software to your CMMS.

    With Mobile Asset Reporting Software, as soon as your Operator enters equipment information into their mobile device, it is saved and forwarded to your Historian, CMMS or other systems of record. This virtually eliminates lag time.

    With your information collection systems in place, you’ll be able to review and analyze your data to help reduce downtime. Your Equipment Downtime Reports will help you identify the most common, and costly, causes of equipment failure. From there, you can take action to prevent and correct equipment failures in your plant, reducing costs and improving profits.

    At GoPlant, we know knowledge is power. We created our Mobile Asset Reporting Software to give you timely, relevant knowledge about your plant, so that you have the power to improve your profits. To see GoPlant in action, Request a Demo.