For manufacturers, unplanned downtime, equipment failure and unexpected outages can have serious effects on manufacturing efficiency. Though external technicians or maintenance teams may work quickly to fix the problem, these events can lead to backlogs in production, wasted resources and delayed orders. Further down the line, these disruptions can have a knock-on effect within your supply chain and be detrimental to customer relationships, along with the cost implications on profit margins.
Maintenance only becomes an issue when downtime is unplanned and/or occurring semi-regularly. With modern manufacturing departments so intrinsically linked by reliant technologies, it’s easy to see how downtime will affect not just one department, but will spread to affect other parts of a manufacturing business. And yet downtime and maintenance is an inevitability in manufacturing. Both machinery and systems have life cycles which require time and resources to maintain. Repairs and wearing of tools and machinery are also a major component of regular maintenance.
The main problem facing these companies is anticipating when their equipment and machinery is due for maintenance ahead of time. Maintaining systems, replacing parts and product upgrades require long-term planning but often due to long life-cycles and inexperience with new equipment, maintenance departments cannot always accurately predict their long-term maintenance schedules.
“More than two-thirds (70%) of companies lack full awareness of when their equipment is due for maintenance, upgrade or replacement.” – The Manufacturer.
In order to avoid disruption within the production process, the latest technology allows the modern manufacturer to foresee maintenance issues and be proactive in their address of upcoming events.
Predictive maintenance in manufacturing
Manufacturing in Industry 4.0 requires unprecedented levels of efficiency, maximising capacity for production using the least resources in the least amount of time and new technologies are constantly evolving to make this possible. It’s for this reason that modern manufacturers cannot afford unplanned downtime as it leaves their business vulnerable. This is why predictive maintenance and planned scheduling based on meaningful data is a valuable asset to take advantage of.
Most reactive maintenance events are predictable, particularly as sensors, analytics and IoT technology become more affordable, accessible and widely understood. Using data insights and predictive analytics to find and track failure patterns and alert you of upcoming problems drive your maintenance strategy. By anticipating failure, preparation can be put in place to prevent or limit disruption by planning the best actions before they happen.
“What used to be a manual, time-intensive procedure can now be dynamic, rapid and automated. IoT-enabled predictive maintenance solution take advantage of streaming data from sensors and devices to quickly assess current conditions. Recognise warning signs, deliver alerts and automatically trigger appropriate maintenance processes.” - Microsoft
Predictive maintenance allows you to limit, control and minimise the resources used in maintenance, maximises your systems' up-time and prevents costly disruption to your business. You can predict failure, set accurate maintenance schedules, order parts and manage technicians. There are many benefits associated with predictive maintenance when used as a maintenance strategy. As maintenance is performed when failure is likely to occur, there is high cost savings related to the production hours lost to maintenance, expenses related to parts and supplies and the time for the equipment to be fixed. Predictive maintenance can minimise issues with reliability or quality. It can help in preventing expensive failures from occurring. Overstock can also be reduced in inventory thanks to predictive maintenance.
Applying predictive maintenance
It’s vitally important, in the current climate, to include intelligent maintenance in your annual business objectives as it plays a crucial role in keeping running costs low, anticipating and planning for failures and creating proactive planned work orders. It need to be applied to your entire operation so that it causes minimal disruption, can be included in master scheduling and material requirements planning and production capacity plans. This is all about staying in complete control of your processes.
Predictive planning requires machinery to be connected to sensors and control systems. The data which is collected by the sensors is transferred to your IT system and then artificial intelligence (AI) converts this into meaningful data to create maintenance plans based on its predictive analysis which can then create works orders or initiate OT (Operational Technology) changes. These will then be communicated across departments affected by the results such as capacity planning and production scheduling which take this data into account and make the necessary adjustments.
“Modern machinery is designed to repeat operations continuously with zero error. When connected to digital platforms which provide such machinery with operational instructions and signals, core applications will work night and day producing high quality items every time. Machinery wear does occur (e.g cutting blade edges lose sharpness and need changing) but, so long as this has been built into the operational plan, it will have no affect at all (predictive maintenance). Downtime does occur but as long as contingency has been catered, again this will have no affect whilst the machinery is repaired and put back into full time operation.” – John Ewing, Head of Sales at Syscom
To begin adopting predictive maintenance, planning is of utmost important and your business must have considered and have several infrastructures in place. In order for predictive maintenance to have any real effect, it needs to be connected to a company-wide ERP software system. Maintenance departments commonly operate in silos and data doesn’t make its way from one department to another. With the right software and a holistic view of all your people, processes and systems, you can begin to automate your processes and build a truly smart factory which incorporates production equipment, operational technology, sensors, cloud technology and convert it to meaningful, actionable data using AI (Arficial Intelligence) and BI (Business Intelligence), with planned maintenance for minimal disruption.