{"id":1085,"date":"2025-03-27T02:41:10","date_gmt":"2025-03-27T08:41:10","guid":{"rendered":"https:\/\/limblecmms.com\/blog\/?p=1085"},"modified":"2025-05-30T12:58:19","modified_gmt":"2025-05-30T18:58:19","slug":"start-program","status":"publish","type":"post","link":"https:\/\/limblecmms.com\/blog\/start-program\/","title":{"rendered":"Creating a Predictive Maintenance Program That is Right for You"},"content":{"rendered":"<div class=\"wpb-content-wrapper\"><p>[vc_row kd_background_image_position=&#8221;vc_row-bg-position-top&#8221;][vc_column][vc_column_text css=&#8221;&#8221;]<span style=\"font-weight: 400;\">If someone was trying to convince you <\/span><i><span style=\"font-weight: 400;\">not<\/span><\/i><span style=\"font-weight: 400;\"> to start a <\/span><a href=\"https:\/\/limblecmms.com\/blog\/start-predictive-maintenance-program\/\">predictive maintenance<span style=\"font-weight: 400;\"> program<\/span><\/a><span style=\"font-weight: 400;\">, they might tell you that it is too complicated or expensive to implement. And while those might be valid concerns for some, the adoption of predictive maintenance strategies is <\/span><a href=\"https:\/\/www.marketsandmarkets.com\/Market-Reports\/operational-predictive-maintenance-market-8656856.html\"><span style=\"font-weight: 400;\">only projected to grow<\/span><\/a><span style=\"font-weight: 400;\">.\u00a0<\/span><\/p>\n<h2>Is it hard to start a predictive maintenance program?<\/h2>\n<p><span style=\"font-weight: 400;\">Implementing a PdM program is indeed more complicated compared to starting a <\/span><a href=\"https:\/\/limblecmms.com\/blog\/preventive-maintenance-program\/\"><b>preventive maintenance program<\/b><\/a><span style=\"font-weight: 400;\">. But the real level of difficulty will depend on the level of expertise available at your organization, the complexity of your assets, and the tools you have at your disposal.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The following sections will review the steps, tools, and expertise required to set up and maintain a PdM program.\u00a0 Once those pieces are in place, <\/span><a href=\"https:\/\/limblecmms.com\/strategies\/predictive-maintenance\/\"><span style=\"font-weight: 400;\">predictive maintenance<\/span><\/a><span style=\"font-weight: 400;\"> becomes a much easier job, and one that is worth the return.\u00a0<\/span>[\/vc_column_text][\/vc_column][\/vc_row][vc_row kd_background_image_position=&#8221;vc_row-bg-position-top&#8221;][vc_column][vc_column_text]<\/p>\n<h2>Steps for establishing a PdM program<\/h2>\n<p><span style=\"font-weight: 400;\">Although the <\/span><a href=\"https:\/\/limblecmms.com\/blog\/benefits-of-predictive-maintenance\/\"><span style=\"font-weight: 400;\">benefits of predictive maintenance<\/span><\/a><span style=\"font-weight: 400;\"> are numerous, deployment can be challenging. So, before you start, it is important to have a well-defined plan covering the desired business outcome and project scope. Ideally, you should start small, learn and adjust as you go along, and use the insights gained for further expansion.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Let\u2019s dive into step-by-step best practices for implementing a successful and sustainable PdM strategy.<\/span><\/p>\n<h3><b>Step 1: Identify assets for PdM<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">First, you must determine which assets to include in your predictive maintenance program. This distinction is important for two reasons:<\/span><\/p>\n<ol>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Not all assets deserve to be on a predictive maintenance plan because some won\u2019t be cost effective. Certain assets that are largely expendable, can be placed on basic routine maintenance or allowed to run to failure.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">If this is your first tango with predictive maintenance, you don\u2019t want to complicate things from the start. It is better to focus on a few selected assets and run this as a pilot project.<\/span><\/li>\n<\/ol>\n<p><span style=\"font-weight: 400;\">By checking historical machine records \u2013 maybe over a two or three-year period \u2013 you can identify the assets that are most vital for your business processes and would cause a substantial disruption if they unexpectedly failed.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Some organizations go through a thorough <\/span><a href=\"https:\/\/limblecmms.com\/blog\/how-to-perform-criticality-analysis\/\"><span style=\"font-weight: 400;\">criticality analysis<\/span><\/a><span style=\"font-weight: 400;\"> on their assets for this step. Another quick way to identify such assets is to note:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Assets that demand the most financial and human resources<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Assets with high repair\/replacement costs that also record frequent breakdown incidents<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Equipment which, if it breaks down, limits or halts production or service delivery<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Assets that do not directly impact production, but the repair costs are considerable and\/or take longer to complete<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Machines that are so sensitive or complex that they require \u201cspecialist\u201d attention to get them back online (which often comes along with a big invoice)<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">Assets that meet the above criteria are the best candidates for the PdM program.<\/span><\/p>\n<h3><b>Step 2: Collect and log actionable data<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">Machine records present a valuable and time-saving source of actionable data to help get PdM rolling. Such data offers information about machine behavior that will, to a large extent, determine how you design the PdM model.<\/span><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"img-fluid aligncenter\" title=\"Historical machine data sources\" src=\"https:\/\/limblecmms.com\/wp-content\/uploads\/2019\/04\/Historical-machine-data-sources.jpg\" alt=\"Historical machine data sources\" width=\"640\" height=\"288\" \/><\/p>\n<p><span style=\"font-weight: 400;\">Sources of historical machine data include:<\/span><\/p>\n<p><b>Manufacturer\u2019s information<\/b><\/p>\n<p><span style=\"font-weight: 400;\">New equipment always <\/span><a href=\"https:\/\/limblecmms.com\/blog\/oem-original-equipment-manufacturer\/\"><span style=\"font-weight: 400;\">comes from the OEM with<\/span><\/a><span style=\"font-weight: 400;\"> comprehensive manuals and instructions. This information covers essential details such as:\u00a0<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">What kind of maintenance is required<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">How often it should be done<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">How to perform it safely\u00a0<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">Manufacturers\u2019 instructions form the basis for starting a maintenance plan on each asset.<\/span><\/p>\n<p><b>In-house historical data collection<\/b><\/p>\n<p><span style=\"font-weight: 400;\">Companies that have been keeping accurate maintenance records can quickly gather historical data for each piece of equipment. Machine data can be extracted from:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Hard copy maintenance records and charts<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Your <\/span><a href=\"https:\/\/limblecmms.com\/cmms\/cmms-software\/\"><span style=\"font-weight: 400;\">CMMS software<\/span><\/a><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Software from other departments (e.g., procurement and accounting).<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">For instance, this is how an asset report may look in a <\/span><a href=\"https:\/\/limblecmms.com\/cmms\/\"><span style=\"font-weight: 400;\">Computerized Maintenance Management System (CMMS)<\/span><\/a><span style=\"font-weight: 400;\">:<\/span><\/p>\n<p>&nbsp;<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter \" src=\"https:\/\/limblecmms.com\/wp-content\/uploads\/CMMS-Software-Asset-Management.webp\" width=\"500\" height=\"352\" \/><\/p>\n<p><span style=\"font-weight: 400;\">Metrics like <\/span><b>total costs, future estimated costs,<\/b><span style=\"font-weight: 400;\"> and <\/span><a href=\"https:\/\/limblecmms.com\/metrics\/mean-time-between-failure\/\"><b>MTBF<\/b><\/a><span style=\"font-weight: 400;\"> show how often an asset fails and will help you determine if an asset is worth putting on a predictive maintenance plan.<\/span><\/p>\n<p><b>Leverage staff expertise<\/b><\/p>\n<p><span style=\"font-weight: 400;\">You can get valuable information that may not be available in writing by involving the staff that work with the machines daily, like <\/span><b>maintenance technicians and machine operators<\/b><span style=\"font-weight: 400;\">.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">They already have a working knowledge of each asset and are familiar with many failure patterns. Their input will make it easier to pinpoint the specific problems they face with each asset and how the eventual predictive model can help.<\/span><\/p>\n<h3><b>Step 3: Analyze failures<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">The goal of this analysis is to identify failure modes and patterns of the assets in your PdM program. It is important to focus on establishing the following:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Severity (and effect) of machine failure<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">The frequency of failure<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">The difficulty of identifying the failure<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">One of the most accurate methods for completing this step is <\/span><a href=\"https:\/\/limblecmms.com\/blog\/fmea-and-fmeca\/\"><b>Failure Mode and Effects Analysis<\/b><span style=\"font-weight: 400;\"> (FMEA)<\/span><\/a><span style=\"font-weight: 400;\">. <\/span><i><span style=\"font-weight: 400;\">Failure modes<\/span><\/i><span style=\"font-weight: 400;\"> are the different events or ways in which an asset can fail. FMEA is a product or process reliability analysis tool used to identify failures affecting a system, prioritize corrective actions, and limit failures overall.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">FMEA is a very detailed and thorough process that involves several worksheets and calculations, but the overall process includes the following steps:<\/span><\/p>\n<ol>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">List the normal functions of the assets in your plan<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Consider all potential failures for each asset<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Identify the effect of each failure on the asset itself, and on the people, processes, and systems that rely on it<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Rank the <\/span><b>severity<\/b><span style=\"font-weight: 400;\"> of each failure (usually from 1 to 10)<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Determine the <\/span><b>occurrence<\/b><span style=\"font-weight: 400;\"> of each failure mode<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Assign a ranking for ease of <\/span><b>detecting<\/b><span style=\"font-weight: 400;\"> each failure<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Use those rankings to calculate the risk priority number (RPN) for each failure.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Assign actions to the failures with the highest RPN<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Review and re-rank RPNs as failures decline over time<\/span><\/li>\n<\/ol>\n<p><span style=\"font-weight: 400;\">The result is a prioritized list that guides development of failure predictions for the highest risk assets first.<\/span><\/p>\n<h3><b>Step 4: Choose and implement condition monitoring techniques and equipment<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">Predictive maintenance programs integrate different types of machine information such as performance data, maintenance history, and design data to make timely decisions about maintenance intervention. Gathering all this data requires specific technologies that enable <\/span><a href=\"https:\/\/limblecmms.com\/strategies\/condition-based-maintenance\/\"><b>condition-based monitoring<\/b><\/a><span style=\"font-weight: 400;\">.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Condition-based monitoring is a crucial step in PdM planning process. The goal is to preempt asset failures by placing monitoring sensors on the assets. The sensors collect data and share it with connected systems that analyze it and use it to identify patterns that can be applied to predict future failures and inform your maintenance actions.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">A wide variety of sensors are available, including (but not limited to):<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Thermometers<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Tachometers<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Endoscopes<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Thermal cameras<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Leak detectors<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Accelerometers<\/span><\/li>\n<\/ul>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter img-fluid\" src=\"https:\/\/limblecmms.com\/wp-content\/uploads\/2019\/04\/Condition-monitoring-equipment.jpg\" alt=\"Condition monitoring equipment\" width=\"639\" height=\"426\" \/><\/p>\n<p><span style=\"font-weight: 400;\">The most common condition monitoring techniques used to detect these faults are:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Vibration analysis<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Lubricant analysis<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Infrared thermography<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Ultrasound testing<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Dynamic pressure analysis<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Acoustics testing<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Current and voltage testing<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">Identifying failure modes for your critical assets helps you to choose the appropriate monitoring technique or <\/span><span style=\"font-weight: 400;\">NDT test<\/span><span style=\"font-weight: 400;\"> for each asset.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">For example, vibration analysis is the most commonly used technique for rotating equipment as it can detect the faults that this category of equipment is prone to, such as roller bearing wear, mechanical looseness, gearbox wear, shaft misalignment, and unbalance.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">There are several reputable brands of sensors you could choose, manufactured by companies like Siemens AG, Schneider Electric, Bosch GmbH, ABB, Honeywell, to mention a few.<\/span><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter img-fluid\" src=\"https:\/\/limblecmms.com\/wp-content\/uploads\/2019\/04\/PdM-Company-Rankings.png\" alt=\"PdM company rankings\" width=\"639\" height=\"387\" \/><br \/>\n<i><a class=\"text-center\" href=\"https:\/\/iot-analytics.com\/top-20-companies-enabling-predictive-maintenance\/\" target=\"_blank\" rel=\"noopener noreferrer\">Image source<\/a><\/i><\/p>\n<h3><b>Step 5: Develop algorithms for making failure predictions<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">Next is identifying equipment failure patterns and using them to create algorithms that can predict the failures in your FMEA. This is the core of predictive maintenance, and what happens here will get you the equipment monitoring alerts you need.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The predictive system uses both the information coming from condition monitoring sensors and <\/span><a href=\"https:\/\/www.mathworks.com\/help\/predmaint\/gs\/designing-algorithms-for-condition-monitoring-and-predictive-maintenance.html?searchHighlight=prognostics%20algorithms&amp;s_tid=doc_srchtitle\"><b>prognostics algorithms<\/b><\/a><span style=\"font-weight: 400;\"> to analyze machine data. Let\u2019s take a brief look at how both functions interact:<\/span><\/p>\n<p><b>Condition monitoring<\/b><\/p>\n<p><span style=\"font-weight: 400;\">The data derived from condition monitoring sensors track any behavior changes that may indicate deterioration. It does this by tracking unusual sensor readings to detect faults by comparing sensor data against readings that are considered normal.<\/span><\/p>\n<p><b>Prognostics algorithms<\/b><\/p>\n<p><span style=\"font-weight: 400;\">Prognostics algorithms are used to estimate the remaining time-to-failure (RTTF) or the <\/span><a href=\"https:\/\/www.mathworks.com\/company\/newsletters\/articles\/three-ways-to-estimate-remaining-useful-life-for-predictive-maintenance.html\"><b>remaining useful life (RUL)<\/b><\/a><span style=\"font-weight: 400;\"> of a machine or component. They help forecast failures by comparing the condition of a machine over time. These algorithms can be established using either modeling or machine learning technology, or by combining both.<\/span><\/p>\n<p><a href=\"https:\/\/tdwi.org\/articles\/2017\/06\/26\/5-skills-to-build-predictive-analytics-models.aspx\"><b>Predictive modeling<\/b><\/a><span style=\"font-weight: 400;\"> is initially done by a data scientist who creates predictive models. Then, a machine learning technology is used to update algorithms over time based on sensor data, increasing its predictive capabilities with each asset failure incident until unplanned downtime can almost be eliminated.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Although this process may take a while to perfect, the final result is an automated system that calculates the RTTF, generates alerts when machine conditions deviate from established thresholds, and determines when maintenance intervention should happen.<\/span><\/p>\n<h3><b>Step 6: Deploy to pilot equipment<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">The final step of implementation is to deploy the technology by integrating it into a few selected pilot assets.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">When implementing this technology, it is important to consider whether or not to use local condition monitoring sensors (sensors attached directly to machines) versus cloud-connected devices (sensors that wirelessly connect to a software platform that has the capacity to store large amounts of data). The latter option will provide the capacity for a lot more data which will be necessary as you add more and more assets to your PdM program.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The analysis generated using cloud-based software can then trigger notifications for maintenance based on your preferences.\u00a0<\/span>[\/vc_column_text][\/vc_column][\/vc_row][vc_row content_placement=&#8221;middle&#8221; kd_background_image_position=&#8221;vc_row-bg-position-bottom&#8221; kd_top_separator_style=&#8221;skew-left&#8221; kd_top_separator_height=&#8221;separator-height-small&#8221; kd_bottom_separator_style=&#8221;skew-left&#8221; kd_bottom_separator_height=&#8221;separator-height-small&#8221; kd_top_separator=&#8221;true&#8221; kd_bottom_separator=&#8221;true&#8221; css=&#8221;.vc_custom_1682969576554{margin-bottom: 40px !important;padding-top: 120px !important;padding-right: 40px !important;padding-bottom: 50px !important;padding-left: 40px !important;background: #dde4e8 url(https:\/\/limblecmms.com\/wp-content\/uploads\/cta-laired-hex-4.webp?id=9077) !important;background-position: center !important;background-repeat: no-repeat !important;background-size: cover !important;border-radius: 0px !important;}&#8221; css_tablet_landscape=&#8221;.vc_custom_1682969576554{padding-bottom: 80px !important;}&#8221; css_tablet_portrait=&#8221;.vc_custom_1682969576555{padding-bottom: 80px !important;}&#8221; css_mobile=&#8221;.vc_custom_1682969576555{padding-bottom: 80px !important;}&#8221;][vc_column][vc_row_inner kd_background_image_position=&#8221;vc_row-bg-position-top&#8221;][vc_column_inner]<header class=\"kd-section-title col-lg-12 text-center  subtitle-below-title kd-animated fadeIn   vc_custom_1682969598832\" data-animation-delay=200><h2 class=\"separator_off\" style=\"font-size: 42px;font-weight: 500;margin-bottom:30px;\">Checklist for Creating a Preventive Maintenance Plan<\/h2><h6 class=\"subtitle\" style=\"color: #152232;\">Following a consistent Preventive Maintenance Plan can make life easier. Use this checklist to create your own!<\/h6><\/header>[\/vc_column_inner][\/vc_row_inner][vc_row_inner content_placement=&#8221;top&#8221; kd_background_image_position=&#8221;vc_row-bg-position-top&#8221;][vc_column_inner width=&#8221;1\/2&#8243; css=&#8221;.vc_custom_1631866454223{padding-right: 50px !important;padding-left: 0px !important;}&#8221; offset=&#8221;vc_col-lg-6 vc_col-md-12 vc_col-xs-12&#8243; css_tablet_landscape=&#8221;.vc_custom_1631866454223{padding-right: 0px !important;}&#8221; css_tablet_portrait=&#8221;.vc_custom_1631866454223{padding-right: 0px !important;}&#8221; css_mobile=&#8221;.vc_custom_1631866454224{padding-right: 15px !important;}&#8221;][vc_raw_html]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[\/vc_raw_html][\/vc_column_inner][vc_column_inner width=&#8221;1\/2&#8243;][vc_single_image source=&#8221;external_link&#8221; alignment=&#8221;center&#8221; css_animation=&#8221;fadeIn&#8221; custom_src=&#8221;https:\/\/3975608.fs1.hubspotusercontent-na1.net\/hubfs\/3975608\/Content%20Downloads\/PM%20Checklist%20mockup.png&#8221;][\/vc_column_inner][\/vc_row_inner][\/vc_column][\/vc_row][vc_row kd_background_image_position=&#8221;vc_row-bg-position-top&#8221;][vc_column][vc_column_text]<\/p>\n<h2><span style=\"font-weight: 400;\">Is your facility ready for a predictive maintenance program?<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">While PdM represents a compelling proactive approach to maintenance, it does have a barrier to entry.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Let\u2019s review the requirements you should have in place if you are serious about implementing a predictive maintenance program:<\/span><\/p>\n<h3><b>Upper management support<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">Starting a predictive maintenance program is a big step forward for any facility and is not a project you want to run without having strong support from upper management. You will need funding, help from other departments, and possibly even a third-party consultant. You don\u2019t want to be left stranded in the middle of the implementation process.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Setting up a pilot project and laying down realistic expectations can go a long way toward getting the necessary approval from the people in charge.<\/span><\/p>\n<h3><b>Appropriate funding<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">Having a flexible budget to invest in technology and expertise is a big bonus, as you will need to:\u00a0<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Buy sensor monitoring equipment<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Invest in a CMMS or other specialized software<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Possibly hire external data scientists to help with creating predictive models<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Spend resources on training technicians<\/span><\/li>\n<\/ul>\n<h3><b>The right condition monitoring equipment<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">The real power of predictive maintenance hides behind two simple concepts:\u00a0<\/span><\/p>\n<ol>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">The ability to monitor the condition of your assets in real-time\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Feeding that data into complex algorithms that allow you to schedule necessary repairs and replacements correctly<\/span><\/li>\n<\/ol>\n<p><span style=\"font-weight: 400;\">Without appropriate condition-monitoring equipment, the algorithms won\u2019t have enough data to do their job correctly and give you accurate predictions and alerts.<\/span><\/p>\n<h3><b>Access to the right software and analytics<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">Arguably the most important requirement for PdM is ensuring you have the right platform for storing and analyzing machine data. It is not rare that businesses look for outside help with this part of the process.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">A CMMS is crucial to creating and running your PdM program by helping you schedule and oversee all maintenance activities \u2013 from ensuring you have the necessary spare parts when you need them to tracking task progress and maintenance costs.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">More advanced CMMS solutions can even be configured to automatically create tasks depending on the incoming sensor data.\u00a0 <\/span><span style=\"font-weight: 400;\">In addition, some organizations might also need to look into employing <\/span><a href=\"https:\/\/limblecmms.com\/blog\/predictive-maintenance-analytics\/\"><b>advanced predictive analytics<\/b><\/a><span style=\"font-weight: 400;\"> that will help them with the creation of necessary predictive models.<\/span><\/p>\n<h3><b>Training requirements<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">While a lot of condition monitoring sensors can be connected to software like a CMMS, some CM equipment might need manual input and monitoring from your maintenance teams who need to know how to use it.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Additionally, no matter which <\/span><a href=\"https:\/\/limblecmms.com\/blog\/maintenance-strategy\/\"><b>maintenance strategy<\/b><\/a><span style=\"font-weight: 400;\"> you\u2019ve been using, a move towards predictive maintenance will require some workflow changes and shifts for the scope of the whole maintenance department.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">This is yet another reason why starting with a pilot project is a good idea \u2013 it gives everyone enough time to get familiar with all of the necessary changes.<\/span><\/p>\n<h2><span style=\"font-weight: 400;\">A switch to predictive maintenance<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Managers often like to wait for the right time to switch to predictive maintenance, which is understandable, considering it can be a big project. But if you\u2019re on top of most of the requirements necessary to begin a PdM program, you should be able to begin a pilot project and work on addressing what you\u2019re missing as you go. And the sooner you start, the sooner you begin to reap the benefits of predictive maintenance.<\/span>[\/vc_column_text][\/vc_column][\/vc_row]<\/p>\n<\/div>","protected":false},"excerpt":{"rendered":"<p>[vc_row kd_background_image_position=&#8221;vc_row-bg-position-top&#8221;][vc_column][vc_column_text css=&#8221;&#8221;]If someone was trying to convince you not [&hellip;]<\/p>\n","protected":false},"author":24,"featured_media":29421,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[734],"tags":[],"class_list":["post-1085","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-predictive-maintenance"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v25.7.1 (Yoast SEO v25.7) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Creating a Predictive Maintenance Program | Limble CMMS<\/title>\n<meta name=\"description\" content=\"Everything you ever needed to know about predictive maintenance programs and how it can help improve your maintenance operation today. Learn more.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/limblecmms.com\/learn\/predictive-maintenance\/start-program\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Creating a Predictive Maintenance Program That is Right for You\" \/>\n<meta property=\"og:description\" content=\"A step-by-step guide that explains how to start a predictive maintenance program and discusses prerequisites for successful implementation.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/limblecmms.com\/learn\/predictive-maintenance\/start-program\/\" \/>\n<meta property=\"og:site_name\" content=\"Limble CMMS\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/limblecmms\/\" \/>\n<meta property=\"article:published_time\" content=\"2025-03-27T08:41:10+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2025-05-30T18:58:19+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/limblecmms.com\/wp-content\/uploads\/blog_template_7.webp\" \/>\n\t<meta property=\"og:image:width\" content=\"1200\" \/>\n\t<meta property=\"og:image:height\" content=\"750\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/webp\" \/>\n<meta name=\"author\" content=\"Bryan Christiansen\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:title\" content=\"Creating a Predictive Maintenance Program That is Right for You\" \/>\n<meta name=\"twitter:description\" content=\"A step-by-step guide that explains how to start a predictive maintenance program and discusses prerequisites for successful implementation.\" \/>\n<meta name=\"twitter:creator\" content=\"@LimbleCMMS\" \/>\n<meta name=\"twitter:site\" content=\"@LimbleCMMS\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Bryan Christiansen\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"11 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/limblecmms.com\/blog\/start-program\/\",\"url\":\"https:\/\/limblecmms.com\/learn\/predictive-maintenance\/start-program\/\",\"name\":\"Creating a Predictive Maintenance Program | Limble CMMS\",\"isPartOf\":{\"@id\":\"https:\/\/limblecmms.com\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\/\/limblecmms.com\/learn\/predictive-maintenance\/start-program\/#primaryimage\"},\"image\":{\"@id\":\"https:\/\/limblecmms.com\/learn\/predictive-maintenance\/start-program\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/limblecmms.com\/wp-content\/uploads\/blog_template_7.webp\",\"datePublished\":\"2025-03-27T08:41:10+00:00\",\"dateModified\":\"2025-05-30T18:58:19+00:00\",\"author\":{\"@id\":\"https:\/\/limblecmms.com\/#\/schema\/person\/a3ef98afa60af6b427b9f68b67eaadd5\"},\"description\":\"Everything you ever needed to know about predictive maintenance programs and how it can help improve your maintenance operation today. 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