{"id":192697,"date":"2022-11-02T08:38:59","date_gmt":"2022-11-02T12:38:59","guid":{"rendered":"https:\/\/fiix.wpengine.com\/?p=192697"},"modified":"2022-11-02T08:38:59","modified_gmt":"2022-11-02T12:38:59","slug":"four-red-flags-in-maintenance-data","status":"publish","type":"post","link":"https:\/\/fiixsoftware.com\/blog\/four-red-flags-in-maintenance-data\/","title":{"rendered":"Four red flags in your maintenance data and 33 ways to fix them"},"content":{"rendered":"

[vc_row][vc_column width=”1\/1″][vc_column_text]<\/p>\n

\n

Data doesn\u2019t always paint a pretty picture<\/h2>\n

The end of the movie The Big Short is a big downer. The main characters come out on top. They\u2019re rich. They\u2019re proven right. They get everything they wanted. <\/p>\n

But while they celebrate, the world descends into chaos. It finally dawns on them\u2014their success will mean disaster for millions of others.<\/p>\n

The main characters are spared the catastrophe because they saw the collapse of the housing market years before everyone else. They recognized the red flags in the data. They trusted numbers over guesses, gut feelings, and assumptions.<\/p>\n

What does this mean for maintenance teams?<\/h2>\n

Somewhere within your maintenance data<\/a> is a tiny alarm bell ringing. It\u2019s telling you that there\u2019s something wrong with your equipment or processes. Silencing that alarm bell now, while it\u2019s faint, is essential. By the time it gets loud enough to be obvious, disaster has struck. That means broken lines, stalled production, high costs, missed orders, and lots of unhappy people.<\/p>\n

But your data is a haystack and those warning signs are a needle\u2014they\u2019re hard to find. That\u2019s why this article is about using maintenance data to pinpoint small issues before they get too big.<\/p>\n

Use this template to help you track key maintenance metrics in one place<\/i><\/a><\/p>\n

But first, when is a problem worth your time?<\/h2>\n

Let\u2019s face it\u2014something will always be broken. A machine that could run better. A component that should be swapped out. The savviest maintenance teams separate the truly troubling from the minor inconveniences and spend their time on the former. <\/p>\n

That\u2019s why there are two questions to ask when you find a worrying number in your data:<\/p>\n

    \n
  1. Is this a one-off anomaly or a trend?<\/li>\n
  2. If it\u2019s a trend, how soon should we address it?<\/li>\n<\/ol>\n

    \u201cYou don\u2019t want to go down a rabbit hole and spend a ton of resources just because you bought one bad controller,\u201d says Mike Cooper, a former engineering manager and current Solutions Engineer at Fiix. <\/p>\n

    Obviously, your first priority is whatever is stopping the line right now. But when that\u2019s fixed, you need to figure out if you\u2019re going to continue fighting that fire or direct your resources somewhere else.<\/p><\/blockquote>\n

    Here\u2019s a handy flow chart to help you make that decision:<\/p>\n

    \n\t\t\"asset
    \n\t<\/figure>\n

    Four troubling trends in your maintenance data and 33 ways to fix them<\/h2>\n

    #1: Rate of corrective work orders issued<\/h3>\n

    What to watch for<\/strong><\/p>\n

    An increase or decrease in corrective work orders on an asset. An uptick in corrective maintenance<\/a> often means equipment is breaking down more than expected. A drop in this number can signal that you\u2019re spending unnecessary labor hours on a task or are missing problems. <\/p>\n

    What\u2019s causing the problem and what to do about it<\/strong><\/p>\n

    If you\u2019re seeing an increase in the rate of corrective work, the culprit is usually in this list:<\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
    \n

    Primary cause<\/p>\n<\/th>\n

    		\n

    Root cause<\/p>\n<\/th>\n

    		\n

    Potential solutions<\/p>\n<\/th>\n<\/tr>\n<\/thead>\n

    A problem is being misidentified<\/strong><\/td>\nTraining gaps<\/td>\nInvest in training for the asset or asset group. Consider hiring a contractor or full-time staff with the missing skillset<\/td>\n<\/tr>\n
    Proper inspections and analysis aren\u2019t being completed<\/td>\nIncrease the frequency of inspections. Create a clear checklist of components to inspect and failure modes to look for. Conduct a full root cause analysis.<\/a><\/td>\n<\/tr>\n
    Incorrect information or data<\/td>\nAudit processes and systems to ensure problems are being reported correctly and meter readings are accurate so you can find the source of broken data.<\/td>\n<\/tr>\n
    A subcomponent is deteriorating quicker than expected<\/strong><\/td>\nThe operating environment has changed<\/td>\nTalk to machine operators, engineers, and plant managers to understand if anything has changed. Adjust your maintenance program accordingly.<\/td>\n<\/tr>\n
    Replacement parts are incorrect or faulty<\/td>\nMake clear labels for parts in your storeroom and\/or build parts kits for the asset. Reconsider your vendor if parts are consistently faulty.<\/td>\n<\/tr>\n
    The machine isn\u2019t operated properly<\/td>\nCreate shared asset SOPs<\/a> between maintenance and operations. Review the SOPs, and their importance, with both teams.<\/td>\n<\/tr>\n
    The asset is nearing its end of life<\/td>\nBuild a business case<\/a> to replace the asset.<\/td>\n<\/tr>\n
    Parts are being rebuilt or replaced incorrectly<\/strong><\/td>\nThe team has outdated or incorrect specs<\/td>\nUpdate the specs and related instructions on work orders and other maintenance material<\/td>\n<\/tr>\n
    The team doesn\u2019t have the right training<\/td>\nInvest in training for the asset or asset group. Consider hiring a contractor or full-time staff with the missing skillset<\/td>\n<\/tr>\n
    Unclear instructions or lack of access to proper resources<\/td>\nGo through work orders with the team and clarify confusing or vague instructions. Make sure the team knows how to access manuals, SOPs, tasklists, and other resources.<\/td>\n<\/tr>\n
    Work is being rushed<\/td>\nGive more time to inspect this asset so technicians don\u2019t feel rushed.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    If the rate of corrective maintenance on an asset drops, make sure it\u2019s not because of these hidden problems:<\/p>\n

      \n
    1. Inspections are too close together: You might be spending budget and labor hours on unnecessary preventive maintenance<\/a>. Maybe you inherited this overstuffed schedule or based it on ultra-conservative OEM recommendations. Whatever the reason, try reducing the frequency of inspections or cutting tasks. You\u2019ll likely gain time in your team\u2019s schedule while seeing no increase in corrective maintenance.<\/li>\n
    2. Inspections aren\u2019t catching a problem: There might be an issue simmering inside an asset, but regular checks are missing it. It hasn\u2019t caused a breakdown\u2026yet. Make sure inspection instructions<\/a> are clear, complete, and specific. Plan for the worst. Kit parts<\/a> for corrective maintenance and create guidelines for emergency work. If a breakdown is coming, you can react quickly and address the root cause after.<\/li>\n<\/ol>\n

      Check out these seven steps for creating a maintenance analytics program from scratch <\/i><\/a><\/p>\n

      #2: Amount of time an asset is offline<\/h3>\n

      What to watch for<\/strong><\/p>\n

      An asset that\u2019s offline longer than usual or an asset that hasn\u2019t been offline for a while. If an asset is offline for long periods, your team might be struggling to manage a particular failure. Equipment that doesn\u2019t go offline for long stretches is probably not getting the maintenance it needs. This could have it on the brink of a huge, disruptive failure.<\/p>\n

      What\u2019s causing the problem and what to do about it<\/strong><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n
      \n

      Primary cause<\/p>\n<\/th>\n

      		\n

      Root cause<\/p>\n<\/th>\n

      		\n

      Potential solutions<\/p>\n<\/th>\n<\/tr>\n<\/thead>\n

      The asset is taking longer to repair<\/strong><\/td>\nEssential skills, training, or resources are missing<\/td>\nInvest in training to fill the gaps. Hire extra staff or contractors to provide the necessary skills. Make sure technicians have manuals, tasklists, and other resources.<\/td>\n<\/tr>\n
      Critical parts aren’t on-hand and\/or are hard to source<\/td>\nIncrease the minimum quantities for these parts. If your company has multiple sites, check if another facility has the parts you need.<\/td>\n<\/tr>\n
      Emergency work and backlog are delaying repairs<\/td>\nAudit your schedule to ensure all work is categorized by priority. Hire a contractor or increase facility shutdowns to help clear backlog. Advocate for extra headcount.<\/td>\n<\/tr>\n
      The root cause of the failure can\u2019t be identified<\/td>\nBring more people into troubleshooting<\/a> and root cause analysis. Diversity of thought helps uncover solutions.<\/td>\n<\/tr>\n
      Maintenance isn\u2019t being notified of problems in a timely manner<\/td>\nCreate shared SOPs and metrics for maintenance and operations to address equipment failure. Invest in a system that allows operators to notify maintenance without having to find a technician.<\/td>\n<\/tr>\n
      Problems are not reported properly<\/td>\nCreate specific guidelines and\/or prompts to help operators describe the problem and possible causes in detail.<\/td>\n<\/tr>\n
      Maintenance isn\u2019t spending enough time on the machine<\/strong><\/td>\nPMs are being missed<\/td>\nMove this work to the top of the schedule and mark it as a high priority. Move it to a different day or time to accommodate other work. Hire a contractor or extra staff to meet deadlines.<\/td>\n<\/tr>\n
      Production is not being stopped for maintenance<\/td>\nAdvocate for more time on the machine. Show schedulers and production managers the cost of potential downtime vs. the cost of regular maintenance.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

      Check out 10 underrated metrics that maintenance teams should be tracking<\/i><\/a><\/p>\n

      #3: Maintenance costs<\/h3>\n

      What to watch for<\/strong><\/p>\n

      Maintenance costs that are higher than expected for an asset. It\u2019s always useful to look at what costs are driving the increase, whether it\u2019s labor, parts, or other resources. You can\u2019t always avoid higher costs (inflation is never fun), but it could mean persistent problems with a machine or process. On the other hand, spending less is notable for different (and better) reasons.<\/p>\n

      \u201cThe mark of a good maintenance program is spending less,\u201d says Kathir Haran, P.Eng, a Solutions Engineer at Fiix with over 10 years of experience in reliability engineering.<\/p>\n

      It means you\u2019re freeing up hours for production. It\u2019s something the maintenance team can point to and show it drove a meaningful improvement.<\/p><\/blockquote>\n

      What\u2019s causing the problem and what to do about it<\/strong><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n
      \n

      Primary cause<\/p>\n<\/th>\n

      		\n

      Root cause<\/p>\n<\/th>\n

      		\n

      Potential solutions<\/p>\n<\/th>\n<\/tr>\n<\/thead>\n

      High labor costs<\/strong><\/td>\nYou\u2019re spending more than usual on contractors<\/td>\nYou may be missing essential skills on the team or there may have been a string of emergencies. Invest in extra training or hire someone to make up for these gaps.<\/td>\n<\/tr>\n
      You\u2019re doing more preventive maintenance than is necessary<\/td>\nIf PMs are not resulting in corrective maintenance, consider scaling back the number of inspections on that asset to save labor hours and costs.<\/td>\n<\/tr>\n
      Data is being logged incorrectly<\/td>\nAudit equipment logs<\/a> to ensure technicians haven\u2019t input the incorrect times. Ensure everyone knows the standard measurements for logging time, like when to round up or down.<\/td>\n<\/tr>\n
      Additional work is being done on a machine<\/td>\nTechnicians may be expanding the scope of work without noting it. Include this work within the scope or clarify why work should be limited to the original instructions.<\/td>\n<\/tr>\n
      Extra technicians are working on the task<\/td>\nReassess the number of technicians assigned to this work or invest in training so technicians feel confident doing the work themselves.<\/td>\n<\/tr>\n
      High parts costs<\/strong><\/td>\nTechnicians are troubleshooting by replacing parts<\/td>\nInvest in training so technicians can identify the right cause of failure. Equip technicians with detailed SOPs, manuals, and failure modes for troubleshooting.<\/td>\n<\/tr>\n
      Emergency purchases are being made<\/td>\nIncrease minimum quantities for these parts so they are always on hand. Kit parts for this asset so you can easily keep track of the parts you have on hand.<\/td>\n<\/tr>\n
      Incorrect parts are used or parts are being replaced incorrectly<\/td>\nMake sure the bill of materials and instructions on work orders are clear and specific. Color-code parts and supplies in your storeroom to match assets. Invest in training.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

      #4: Production levels<\/h3>\n

      What to watch for<\/strong><\/p>\n

      \u201cIt\u2019s simple\u2014if you\u2019re consistently not meeting your production goals, there\u2019s something wrong,\u201d says Thibaut Drevet, MSc, a Senior Solutions Engineer at Fiix and former process engineer.<\/p>\n

      It\u2019s all about how many items you produce every day. If it\u2019s not on target, maintenance has some responsibility for that. There needs to be that connection between maintenance and production.<\/p><\/blockquote>\n

      What\u2019s causing the problem and what to do about it<\/strong><\/p>\n\n\n\n\n\n\n\n\n\n\n
      \n

      Primary cause<\/p>\n<\/th>\n

      		\n

      Root cause<\/p>\n<\/th>\n

      		\n

      Potential solutions<\/p>\n<\/th>\n<\/tr>\n<\/thead>\n

      Low rate of clean startups<\/strong><\/td>\nEquipment specs have changed<\/td>\nAdjust maintenance frequency and instructions if specs have changed. For example, parts may need extra lubrication based on the product going into the machine.<\/td>\n<\/tr>\n
      Parts weren\u2019t repaired, replaced, or rebuilt correctly<\/td>\nReview the bill of materials and instructions on work orders to ensure they\u2019re correct and clear. Make sure all bins, shelves, and areas of your storeroom are labelled properly. Create parts kits for assets. Spend time training technicians and give them better access to diagrams and manuals.<\/td>\n<\/tr>\n
      High levels of scrap and rework<\/strong><\/td>\nComponents are deteriorating<\/td>\nIncrease the frequency of inspections. Monitor the operating context to spot anything that may be affecting components (ie intense cold). Do a repair or replace analysis<\/a> to determine if the asset is at the end of its life.<\/td>\n<\/tr>\n
      Components are repaired, replaced, or rebuilt incorrectly<\/td>\nMake sure the bill of materials and instructions are clear and specific. Color-code parts and supplies in your storeroom to match assets. Invest in training.<\/td>\n<\/tr>\n
      Maintenance delays<\/strong><\/td>\nParts and materials are hard to access<\/td>\nIf technicians spend more time looking for parts than replacing them, consider creating parts kits for equipment. Digitize manuals, asset records, and checklists so your team doesn\u2019t have to visit the office to get them.<\/td>\n<\/tr>\n
      Technicians are having difficulty identifying and\/or troubleshooting problems<\/td>\nMake sure asset records are complete, clear, and accessible. Review FMEAs<\/a> and emergency readiness plans with technicians. Put several technicians on the problem until the root cause is identified.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

      <\/h2>\n<\/p>\n

      Read five ways maintenance teams can help increase production efficiency<\/i><\/a><\/p>\n

      How NOT to spend hours searching for this data<\/h2>\n

      Analyzing maintenance data is a marathon. This article is about the last couple of miles of that race\u2014the part where you\u2019ve already collected the data, set baselines, created reports, and reviewed the numbers. It certainly doesn\u2019t cover everything that happens before you set foot at the starting line, like setting up the right culture, systems, and processes to get the data.<\/p>\n

      There\u2019s a reason people don\u2019t run marathons or build great maintenance analytics programs\u2014they both take a long time and involve a lot of pain.<\/p>\n

      But what if you had a shortcut? A way to cruise through the training and the first 25 miles of the run? Luckily, we created one.<\/p>\n

      It\u2019s called asset insights and it\u2019s part of Fiix Foresight<\/a>, Fiix\u2019s set of AI-powered tools for maintenance teams. Asset insights examines all past work orders for a piece of equipment and learns how it normally operates. That includes everything from how many parts it uses to how much maintenance typically costs, and how much of the work is corrective. It then alerts you if you are over or under these benchmarks.<\/p>\n

      \n\t\t\"asset
      \n\t<\/figure>\n

      Asset insights shows you the telltale signs of asset failure and broken processes in seconds so you don\u2019t need to scroll through an endless spreadsheet or spend hours creating reports. It\u2019s your shortcut to more productive assets, a less crowded schedule, and a healthier bottom line.<\/p>\n

      If you want to learn more about asset insights, check out the Fiix Foresight page<\/a>.<\/p>\n<\/div>\n

      [\/vc_column_text][\/vc_column][\/vc_row]<\/p>\n","protected":false},"excerpt":{"rendered":"

      [vc_row][vc_column width=”1\/1″][vc_column_text] Data doesn\u2019t always paint a pretty picture The end of the movie The Big Short is a big downer. The main characters come out on top. They\u2019re rich. They\u2019re proven right. They get everything they wanted. But while they celebrate, the world descends into chaos. It finally dawns on them\u2014their success will mean disaster for millions of others. The main characters are spared the catastrophe because they saw the collapse of the housing market years before everyone else. They recognized the red flags in the data. They trusted numbers over guesses, gut feelings, and assumptions. What does this mean for maintenance teams? Somewhere within your maintenance data is a tiny alarm bell ringing. It\u2019s telling you that there\u2019s something wrong with your equipment or processes. Silencing that alarm bell now, while it\u2019s faint, is essential. By the time it gets loud enough to be obvious, disaster has struck. That means broken lines, stalled production, high costs, missed orders, and lots of unhappy people. But your data is a haystack and those warning signs are a needle\u2014they\u2019re hard to find. That\u2019s why this article is about using maintenance data to pinpoint small issues before they get too big. Use […]<\/p>\n","protected":false},"author":31,"featured_media":192698,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2,148],"tags":[],"coauthors":[],"class_list":["post-192697","post","type-post","status-publish","format-standard","hentry","category-blog","category-maintenance-strategies"],"yoast_head":"\nFour Red Flags In Your Maintenance Data And 33 Solutions<\/title>\n<meta name=\"description\" content=\"Learn how to find early warning signs of equipment failure and broken processes in your maintenance data, and strategies for solving these problems quickly.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/fiixsoftware.com\/blog\/four-red-flags-in-maintenance-data\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta 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