# Condition Monitoring Program Readiness Assessment > Source: https://netray.co/tools/condition-monitoring-program-readiness-assessment > Publisher: Netray (netray.co), AI and integration engineering for ERP and manufacturing systems. > Section: Free Tools ## Short answer Answer 10 questions about assets, data, skills and follow through to see how ready your plant is for a predictive maintenance program. ## Category maintenance ## Industry Process and Discrete Manufacturing ## Audience - Reliability engineer - Maintenance manager - Plant manager ## Tool **Kind:** assessment **Questions:** #### Do you have a current, criticality ranked asset list? **Help:** Criticality decides where monitoring money goes first. **Options:** ##### No asset list or ranking **Score:** 0 ##### Asset list but no criticality ranking **Score:** 1 ##### Ranking exists for some areas **Score:** 2 ##### Full ranking reviewed in the last year **Score:** 3 #### How well do you know your dominant failure modes? **Options:** ##### We react to breakdowns without analysis **Score:** 0 ##### Technicians know them but nothing is recorded **Score:** 1 ##### Failure codes recorded on work orders **Score:** 2 ##### Failure modes analysed (FMEA or RCM) for critical assets **Score:** 3 #### Which condition monitoring techniques are in use? **Options:** ##### None **Score:** 0 ##### One technique, ad hoc **Score:** 1 ##### Two or more on routes **Score:** 2 ##### Several techniques chosen by failure mode **Score:** 3 #### Are measurement points and routes defined and repeatable? **Options:** ##### No fixed points **Score:** 0 ##### Points are marked but not documented **Score:** 1 ##### Documented routes for some assets **Score:** 2 ##### Documented routes with baselines and limits **Score:** 3 #### Who is trained to collect and interpret the data? **Options:** ##### Nobody **Score:** 0 ##### Vendor does it, we only see reports **Score:** 1 ##### Technicians trained to collect, a few can analyse **Score:** 2 ##### Certified analysts and clear review responsibilities **Score:** 3 #### Where is condition data stored? **Options:** ##### Paper or personal files **Score:** 0 ##### Spreadsheets **Score:** 1 ##### Instrument software with trending **Score:** 2 ##### Linked to the CMMS or ERP asset record **Score:** 3 #### What happens when a reading goes out of limit? **Options:** ##### Nothing defined **Score:** 0 ##### Verbal report to a supervisor **Score:** 1 ##### Notification raised manually **Score:** 2 ##### Defined alarm to notification to planned job **Score:** 3 #### Do you track what the program saves? **Options:** ##### No tracking **Score:** 0 ##### Anecdotes only **Score:** 1 ##### Count of catches recorded **Score:** 2 ##### Avoided downtime and cost recorded per catch **Score:** 3 #### How good is your spare parts and planning for planned repairs? **Options:** ##### Parts are ordered after failure **Score:** 0 ##### Some critical spares kept **Score:** 1 ##### Spares for most critical assets **Score:** 2 ##### Spares and kits linked to planned jobs **Score:** 3 #### Does management support the program? **Options:** ##### No budget or sponsor **Score:** 0 ##### Interest but no budget **Score:** 1 ##### Budget for equipment and training **Score:** 2 ##### Sponsor, budget and reliability targets in place **Score:** 3 **Bands:** #### Reactive **Min:** 0 **Max:** 29 **Verdict:** You are mostly fixing machines after they fail, so a full predictive program would not yet pay off. **Recommendations:** - Build an asset list and rank criticality - Record failure codes on every corrective work order - Start with a small route on the top ten critical rotating assets - Buy training before expensive equipment #### Starting out **Min:** 30 **Max:** 54 **Verdict:** Some monitoring happens, but results depend on individuals and data is not reliably acted on. **Recommendations:** - Document routes, points and baselines - Define who reviews data and by when - Set alert and danger limits from standards and baselines - Link out of limit readings to notifications #### Developing **Min:** 55 **Max:** 79 **Verdict:** You have a working program. The gains now come from connecting data to work management and measuring results. **Recommendations:** - Calculate P-F intervals and tune route frequency - Store condition data against asset records - Record avoided cost for each catch - Extend monitoring to the next tier of assets #### Advanced **Min:** 80 **Max:** 100 **Verdict:** Your program is structured and measured. Focus on automation, online sensing and continuous improvement. **Recommendations:** - Evaluate online sensors on high criticality assets - Automate alarm to work order flow - Review failure data to refine limits and intervals - Share results with finance to protect the budget ## Content **Intro:** Most predictive maintenance efforts fail because of process, not sensors. This short assessment looks at assets, failure knowledge, techniques, skills, data handling and follow through to show where your program stands. **Sections:** #### How to use the assessment **Body:** Answer each of the ten questions for your site as it really is today, not as it is planned. Pick the option that best describes typical practice. If practice varies between areas, choose the lower one, because the weakest link limits results. The score is converted to a percentage and mapped to one of four bands with recommended next steps. Export the result to PDF and use it as a baseline to repeat every six or twelve months. **Bullets:** - Answer honestly, the score is for you - Involve a technician as well as an engineer - Re-run it after each improvement phase - Use the lowest scoring questions as your action list #### What the questions cover **Body:** They follow the path from asset knowledge to value. First, do you know what matters, through criticality and failure modes. Then, can you detect developing faults, through techniques, routes and skills. Next, can you act on them, through alarms, notifications and spares. Finally, can you prove the result, through tracking and management support. A gap at any step wastes the investment before it, which is why a program with expensive sensors but no planned response disappoints. #### Reading your band **Body:** Reactive and starting out sites should resist the urge to buy a platform and instead fix basics such as the asset hierarchy and failure coding. Developing sites usually gain most from integrating data with work management and learning P-F intervals from their own history. Advanced sites can justify online monitoring and analytics, but should still validate alerts against real findings to avoid alarm fatigue. #### Common mistakes **Body:** Buying technology before choosing which failures to detect is the classic error. Another is monitoring everything equally instead of by criticality. Programs also stall when the person who collects the data is not the one who decides on repairs, so make roles explicit. Finally, many teams never record the savings, so the budget disappears at the first cost cutting round. **Cta:** If you want help connecting condition data to your ERP asset and work order structure, Netray can review your setup and suggest a practical first step. **Faq:** #### What is condition-based maintenance? **Answer:** It is a strategy where maintenance is triggered by the measured condition of equipment rather than by a calendar or a failure. Techniques include vibration, oil analysis, thermography and ultrasound. It works best on failure modes that develop gradually and give warning. #### Do I need sensors to start predictive maintenance? **Answer:** No. Many sites start with handheld instruments and manual routes on the most critical rotating equipment. Online sensors make sense later for assets where the P-F interval is short, access is difficult or failure consequences are severe. #### How long does it take to build a condition monitoring program? **Answer:** A basic route on critical assets can start within weeks. Reaching a reliable program with trained staff, limits, alarms and savings tracking typically takes a year or more, depending on how much groundwork on assets and failure data is needed. #### Which assets should I monitor first? **Answer:** Start with the ones whose failure causes the greatest production, safety or cost impact and which have failure modes that give warning, such as critical pumps, fans, compressors and gearboxes. Criticality ranking from your asset data guides the list. ## Search terms condition monitoring maturity assessment, predictive maintenance readiness checklist, predictive maintenance assessment, condition monitoring program audit, reliability maturity assessment, pdm program readiness, how to start predictive maintenance, condition based maintenance maturity --- Talk to an engineer: https://netray.co/contact?intent=erp_ai | Machine catalog: https://netray.co/agent/catalog.json