The prescriptive maintenance market is surging, with forecasts suggesting that this sector will increase in value by a quarter each year over the course of the next decade. The closely related field of predictive maintenance is experiencing a similarly steep ascent, projected to grow annually by more than 30% until 2031.
Both maintenance strategies are effective ways of improving operational efficiency and minimising downtime, but there’s a distinct difference between the two: predictive maintenance uses data analytics and machine learning (ML) to anticipate equipment failures before they happen, while prescriptive maintenance goes a step further, offering actionable recommendations to pre-empt and prevent future disruptions.
Bartek Roszak, Head of AI at STX Next, a global leader in IT consulting, believes that the right choice between a predictive or prescriptive approach varies from company to company, as the latter requires more advanced AI and ML capabilities that can be expensive and complex to implement.
Roszak said: “Effective maintenance strategies are crucial for maintaining efficiency and continuity of machinery in today’s competitive industrial landscape. As organisations face pressure to optimise performance and reduce costs, advanced maintenance techniques have taken centre stage.
“The adoption of predictive and prescriptive maintenance offers a competitive edge by enabling a shift from reactive to proactive strategies. Utilising real-time data, advanced algorithms and IoT sensors, these methods help mitigate risks, cut costs, enhance safety, and extend the lifespan of assets.
“Despite the higher complexity and cost, prescriptive maintenance offers more comprehensive decision-making support. While predictive maintenance provides valuable insights into when a failure might happen, prescriptive maintenance goes beyond, offering actionable steps following the analysis of data patterns. These steps can include root cause analysis, optimal repair schedules and even operational adjustments designed to prolong equipment life.
“Choosing between predictive and prescriptive maintenance hinges on a range of factors, including industry requirements, financial resources, existing infrastructure and long-term goals. While prescriptive maintenance provides deeper insights and better decision support, its complexity and higher costs may not be feasible for all businesses. Good planning and budgeting are crucial in this respect.”
Roszak concluded: “Businesses that operate in capital-intensive industries must consider a maintenance strategy that is intuitive and allows them to operate on the front foot. Identifying which approach best suits the needs of the organisation – before rushing into development integration – is a vital aspect of modernising the upkeep of machinery.”
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