Predictability in an Unpredictable Economy
20 June 2023
20 June 2023
Asset maintenance is undertaken in any equipment-centric industry, and involves condition monitoring of machinery, repairs, and the scheduling of future assessments and repairs. Typically, the practice looks at key operating variables of an asset, such as product flow; temperature; vibration; and pressure, as well as interdependencies across these, with a view to improving effectiveness.
The scope of maintenance strategies of course varies substantially depending on the scale, industry and complexity of the work environment, as well as safety parameters and considerations. However, all maintenance strategies share a common goal, which is to minimise costs and equipment breakdown, reduce risk, and boost production efficiency. Organisations can ill afford to suffer loss of production, and associated operating costs and reputational damage, as a result of ineffective equipment maintenance.
Such is the potential value of getting this practice right, we’re in the midst of a predictive maintenance revolution with the global predictive maintenance market set to increase in value from $4.270 billion in 2020 to $22.429 billion by 2026
As we see more businesses turning towards Industry 4.0, it makes total sense that predictive maintenance will become standard best practice. In fact, Gartner predicts that by 2026, 60% of IoT enabled predictive maintenance solutions will be delivered as part of enterprise asset management products, up from 15% in 2021.
Through deploying the right set of tools and strategies companies can leverage the mountains of data available via manual inspections, temperature and noise monitoring, sensors and cameras to establish patterns and spot anomalies, in order to keep equipment and production lines in peak operating condition.
There is no one-size-fits-all asset management model. However, any organisation which is using anecdotal information from which to manage complex, high-tech assets, is arguably on borrowed time. Adopting predictive maintenance capabilities which facilitate visibility of asset performance, is crucial for all plants.
While equipment-heavy manufacturers may require more extensive or in-depth capabilities, those at the start of their predictive maintenance journey might not yet require a dedicated EAM system. In fact, they may be able to source the right levels of functionality within their existing ERP platform.
Advanced Plant Maintenance (APM) for example is an extension to ERP, and in conjunction with Infor CloudSuite Industrial, it allows you to make sense of asset data, to develop a more profound understanding of assets, predict and prevent failures, and improve failure management. This in turn improves budgeting and cost control—all without having to install, then try to manage and maintain multiple software operations.
By leveraging plant maintenance capabilities as part of ERP, manufacturers can benefit from a 360° view of financials, sales, operations and more. As well as being a highly scalable fully-integrated system, such a platform digitises maintenance with built-in industry specific capabilities.
For example, if a purchase order is raised, it automatically goes into a comprehensive workflow system, with purchase orders (PO) created automatically. Once a PO is approved, it’s then automatically replicated and inventory is issued. You benefit from a traceable, auditable and transparent view, bringing new levels of efficiency and visibility to the business without the cost, expense and complexity of intensive and sometimes ineffective integration projects.
Infor SyteLine (CloudSuite Industrial)
Looking ahead, machine learning and AI will undoubtedly play a much bigger role in predictive maintenance. Whether it is part of ERP, EAM or a dedicated predictive analytics capability, with the right solutions in place, the numerous factors that determine and affect an asset’s condition can be evaluated, informing maintenance plans accordingly.
As recent years have demonstrated, predictive maintenance is rapidly becoming synonymous with best practice as businesses realise multiple benefits right across the organisation. With predictive maintenance proving key to increasing not only productivity, but sustainability efforts and, ultimately, profitability, it’s no longer a case of whether to invest, rather which route to take, how extensive capabilities need to be for your organisation, and when.
For more information on how the Inforlogic support team can guide your business through the digital adoption process, get in touch or call the team on 01606 720499.
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