Traditionally, companies repaired machinery and equipment only after it had already broken. This approach is called reactive maintenance and is problematic as it disrupts operations and leads to substantial losses. Reactive maintenance also leads to subpar equipment efficiency. To ensure optimal overall equipment efficiency, companies are encouraged to plan maintenance activities based on accurate data pertaining to the status of the assets, rather than based on hypothetical end of life values. To this end, manufacturers worldwide are increasingly recognising the advantages of Industry 4.0 in their manufacturing operations and as a potential value-added service to their clients. Here are 3 reasons why:
1. Automate processes using connected devices
2. The ability to collect and share information
3. Predictive maintenance offers several benefits
Manufacturers’ customers, on the other hand, often lack the ability and skills to either build or refine machine learning models for highly accurate predictive maintenance. It would therefore make sense for manufacturers to equip their machinery and equipment with a predictive maintenance solution powered by machine learning and artificial intelligence (AI) from the start and so provide increased value to their clients. This will not only support clients adopting Internet of Things (IoT) and machine learning technologies but will also accelerate their Industry 4.0 strategies and optimise their operations without the expert human analyses that are normally required. Fitting machinery and equipment with a predictive maintenance model has the potential to create a recurring revenue stream for manufacturers and provides a substantial value-add to their clients.
1. Automate processes using connected devices
At the heart of Industry 4.0 lies the ability to automate processes using connected devices that can collect, send, and receive data. Manufacturers are increasingly realising the value that machine learning and AI can bring to the machinery and equipment that they build. This value is much more than just analytics; it also supports clients’ overall smart manufacturing plans. These technologies can help clients achieve the goals of Industry 4.0 and assist them to be more responsive to market demand without it placing an additional financial burden on them. Smart sensors ultimately drive Industry 4.0 and IoT in factories and workplaces. This combined with increased computational power has the potential to enable innovative ways of analysing data and gaining actionable insights. Sensors can be installed on rotating equipment such as motors, gearboxes, fans, and pumps to measure vibration and temperature, and securely transfer the data to cloud storage for analysis. This, in turn, can improve several operational areas resulting in responsive and agile production, and enhanced performance across various industrial sectors.
2. The ability to collect and share information
Interconnected automation requires connected machines to collect and share information. How these machines communicate through networks makes Industry 4.0 possible. Industry 4.0 in manufacturing (also referred to as Manufacturing 4.0) is driven by capital, assets, and operational efficiency. When implemented properly, Manufacturing 4.0 will deliver improved information and automation, and the ability to intervene on a predictive basis leveraging the five different layers of IoT systems integration (connected sensors, centralised data, actionable insights, workflow automation and predictive insights). In fact, the combination of smart sensors and AI means that sensors can eventually become self-testing and will be able to monitor and improve their own performance and so reduce instances of corrupted data. The best possible industrial processes will progressively include sensors that warn of imminent damage before a failure occurs.
3. Predictive maintenance offers several benefits
Downtime is still the single largest cause of lost production time for most manufacturers. According to AspenTech, “[t]he vast majority of manufacturing downtime is caused by process or equipment failures. These emergent causes of unplanned downtime account for 80% of manufacturing downtime.” Implementing predictive maintenance offers several benefits such as:
- reduced maintenance costs and improved production;
- maximised machinery and equipment lifespans;
- decreased downtime and lost-time incidents;
- enhanced customer service; and
- increased revenue as predictive maintenance protects your valuable assets.
Predictive maintenance, when implemented correctly, can help you avoid costly repairs and equipment downtime and save your business millions of rands. In fact, downtime as a result of machine failures can be more costly than the actual machines breaking. The question, therefore, becomes: Can you afford not to implement predictive maintenance in your manufacturing operations?
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How predictive maintenance can reduce manufacturing breakdowns by up to 75%
