WHY ARE THE TOP PLAYERS ENCOURAGING THE DEVELOPMENT OF PREDICTIVE MAINTENANCE?

In 2019, Europe held the largest share of the predictive maintenance market. The growth of IoT connectivity, increasing investment in predictive maintenance, and growth in the automotive sector are among the factors likely to drive the market growth during the forecast period. In addition, companies such as Robert Bosch GmbH, Schneider Electric SA, and SAP SE are encouraging the development of predictive maintenance solutions in the region.

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IBM, SAS, GE DIGITAL, SCHNEIDER, TIBCO SOFTWARE AND SOFTWARE AG – PROMINENT MARKET

Unplanned outages can disrupt the production process and cause unsatisfactory results. Such incidences can cause huge financial loss not just in the manufacturing industry but also in logistics, and passenger and freight transport. For example, in Germany, roughly a quarter of all trains arrive behind schedule. This is a significant disadvantage for passengers and freight customers. Also, delays in extremely tight schedules and crowded networks have a ripple effect that affects the entire system’s programs. Studies show that defects cause more than one-third of initial delays in rolling stock and infrastructure components; in other words, they are caused by unexpected failures in the metro, train, etc.

Over 80% of European manufacturers and transportation operators plan to increase their expenditure on predictive maintenance solutions over the next two years to redefine their maintenance processes and improve operational efficiency. To optimize the maintenance processes of assets, European manufacturers and transportation operators turn to digital technologies such as the Internet of Things or predictive maintenance to allow vast amounts of operational data to be collected, which can be used to predict failures of their machinery and vehicles.

Predictive maintenance is a technique that evaluates the condition of an enterprise's machines and equipment to prevent failures during operation. It uses predictive algorithms with sensor data to estimate the possibility of equipment failure. It also identifies the root cause of complex machinery problems and helps determine which part requires repair or replacement. This minimizes the downtime and maximizing the life of the equipment. Predictive maintenance is a process of monitoring equipment through the operation to identify any deterioration, which allows carrying out maintenance by reducing operating costs. It is commonly used in Industry 4.0 framework. The primary goal of predictive maintenance is to deliver the most precise maintenance planning in advance to avoid unforeseen failures.

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