Supply chains are complex networks, where many different businesses and entities work together to transport goods around the world. At the heart of this system is advanced supply chain equipment, which supports everything from inventory software to the physical assembly of products. This equipment is susceptible to unexpected breakdowns, which can then trigger a domino effect that leads to disrupted production, delayed shipments, and eroded customer satisfaction. Instead of being caught off-guard by unplanned equipment failures, inventory-based businesses can use predictive maintenance to anticipate when problems might occur, optimize maintenance schedules, extend equipment life, and reduce costly downtime.
Understanding Predictive Maintenance
Predictive maintenance is a proactive approach to equipment management and repair, which uses data and analytics to predict when equipment is likely to fail. Unlike reactive maintenance, which responds to breakdowns, or preventive maintenance, which follows a fixed schedule, predictive maintenance is based on the real-time condition of equipment.
How exactly does predictive maintenance work? This advanced strategy relies on a combination of real-time monitoring of equipment performance (using sensors), as well as sophisticated data analytics tools. By analyzing this data, inventory-based businesses can identify patterns and anomalies that will likely indicate potential issues. For example, a sensor might detect things such as unusual vibrations, temperatures, and pressure levels in equipment. If these metrics begin to deviate from normal operating parameters to levels that are concerning, it could signal an impending failure.
In this way, predictive maintenance allows you to intervene and schedule repairs before a breakdown occurs, minimizing downtime and preventing costly emergency repairs.
Impact of Unplanned Equipment Downtime on Supply Chains
Without predictive maintenance, equipment can experience unplanned downtime, which can be more time-consuming and costly to repair. And in general, equipment downtime can greatly hinder supply chain efficiency. Data shows us that unplanned downtime costs industrial manufacturers as much as $50 billion a year, and that more than 80% of companies fail to calculate their downtime costs correctly.
What are some of the impacts of unplanned equipment downtime on supply chains?
- Lost production: When equipment is unexpectedly sidelined, it results in lost production output, directly impacting revenue.
- Increased labor costs: Unexpected equipment failures can require businesses to pay employees to work overtime and more urgently to expedite repairs. Additionally, if workers are idle due to equipment failures, resources are being wasted.
- Customer dissatisfaction: Product shortages and other production issues from expected equipment failures can lead to delayed and even missed deliveries, which can then erode customer trust and loyalty.
- Reputational damage: Frequent equipment failures and their impacts can damage a company’s reputation for reliability and efficiency.
Instead of being caught off-guard by unplanned equipment failures, you can use predictive maintenance to anticipate when and where equipment failures are likely to occur, so you can take action to quickly and efficiently repair equipment.
The Role of Predictive Maintenance in Improving Operations
Predictive maintenance is a game-changer when it comes to improving warehouse and business operations. By anticipating potential failures rather than reacting to them, businesses can significantly reduce the frequency and impact of unplanned outages.
Here is how predictive maintenance contributes to better operational excellence.
1. Proactive issue identification and resolution
Predictive maintenance systems continuously monitor equipment performance, identifying subtle deviations from normal operating parameters, and ignaling potential issues. Then, by analyzing historical data and real-time sensor information, maintenance teams can not only solve issues before they occur, but also pinpoint the root causes of equipment problems to prevent recurring failures.
2. Optimized maintenance schedules
Predictive maintenance enables the creation of precise maintenance schedules based on the actual condition of equipment, rather than arbitrary repair schedules. This maximizes equipment uptime, as well as repair resource allocation: instead of occupying your team with unnecessary repairs, they’ll be assigned to necessary repairs.
3. Cost savings and efficiency gains
By addressing issues before they escalate into major breakdowns, you can likely reduce the amount of downtime, and significantly lower repair expenses. For example, studies show that companies can save up to 18% by using preventive maintenance strategies and over-reactive strategies.
4. Improved equipment reliability and performance
By preventing premature equipment failure, predictive maintenance extends the lifespan of equipment, while reducing the need for expensive replacements. Plus, optimized maintenance schedules and early issue detection can enhance overall equipment reliability and performance.
Ultimately, predictive maintenance is a strategic investment in your operations that can minimize downtime, optimize maintenance efforts, and extend the life of your equipment.
How to Build a Predictive Maintenance Program in Your Organization
Implementing a predictive maintenance program requires careful planning and execution. Here’s a roadmap you can use to guide you through the process in your organization.
1. Define your predictive maintenance goals
First, outline how predictive maintenance will contribute to your overall business objectives, and what metrics you will use to monitor success. Goals might include increasing equipment uptime and reducing maintenance costs, while metrics might include time between failures and time to repair.
2. Conduct an asset assessment
Next, determine which equipment is the most critical, and has the greatest impact on your operations and production. Be sure to collect detailed information about each asset including age, usage patterns, maintenance history, and previous failures.
3. Build a strong data foundation
Data is the root of your predictive maintenance efforts, so you must be collecting useful and accurate data on your equipment. For example, you might need to equip critical assets with sensors to capture real-time data on equipment performance and condition, and deploy predictive data analytics tools that can help you distill insights from your historical and real-time data.
Also, ensure your predictive maintenance technology integrates with your current systems, including your enterprise resource planning (ERP) solution and inventory management systems, for seamless data flow and coordination.
4. Optimize maintenance schedules based on conditions
Now that you have robust data, you can adjust your maintenance schedules based on the actual condition of the equipment. You can plan repairs for optimal times which limit the impact on your operations and customers, and create contingency plans to compensate for planned equipment maintenance.
5. Continuously improve your maintenance program
After launching your predictive maintenance program, you can continuously monitor and improve it. For example, you can provide your maintenance teams with training and development opportunities, so they have the skills and knowledge to effectively utilize predictive maintenance tools and technologies. You can also leverage the latest advancements in predictive maintenance, such as advanced forecasting and analytics tools.
Additionally, regularly review the performance of your predictive maintenance system, and compare it against your initial goals. Look for ways to collect better data, improve your repair processes, and even further reduce operational downtime, for example.
By understanding what predictive maintenance is and how to best deploy it, businesses can both reduce equipment downtime and improve reliability. When predictive maintenance is used properly with sensors and advanced analytics, it can lead to proactive issue resolution, optimized maintenance schedules, and cost savings for businesses.
StockIQ: Your Supply Chain Planning Partner
Predictive maintenance requires an abundance of data, and if you’re looking for an advanced supply chain planning tool to support your operations, StockIQ is here to help. StockIQ is an advanced supply chain planning suite that allows you to control inventory, simplify ordering, and improve demand forecasting.
If you’re ready to unlock the power of streamlined supply chain management contact us today, or request a StockIQ demo.
