November 2019

52 | Plant & Works Engineering www.pwemag.co.uk November 2019 Production Engineering SPECIAL FOCUS T oday’s customers overwhelmingly favour the simplicity of subscription models, where they pay a flat monthly fee for access to a product in the form of a service. For example, consumers no longer buy or rent DVDs, they subscribe to Netflix; more of them prefer services from Uber or Lyft over traditional car ownership. As these digital- age consumers enter the industrial workforce in large numbers, they are causing a redefinition of business models, leading to an increased trend towards subscription-based services in manufacturing industries. This shift towards a subscription-based business model in the manufacturing industry is being referred to as servitisation, where manufacturers no longer strictly sell new products, but instead sell access to and the outcome those products deliver. This new way Reshaping manufacturing Regardless of industry or vertical, companies around the world are encountering a new generation of customers with ever-evolving expectations, and these new demands are forcing brands to redefine the way they do business. Syncron’s Vivek Shah takes a look at how machine learning and predictive analytics are reshaping manufacturing. of delivering services is forcing manufacturers to shift to subscription-based pricing models, where Product-as-a-Service (PaaS) becomes the norm. Manufacturers of complex industrial equipment, because they operate in a B2B environment, can attribute this shift to another major cause: their customers are also dealing with complex operating paradigms, forcing them to improve productivity and capital utilisation. In these scenarios, customers are looking to simplify their businesses, and increasingly favour suppliers who can help minimise their risks in operating a profitable business. The full realisation of servitisation – which could take up to 15 years – especially impacts manufacturers’ after-sales service organisations (the service delivered after the initial sale of a product). In today’s current reactive, break-fix service model, the responsibility of maintenance and ensuring equipment availability falls on the customer. In a servitisation model, however, manufacturers will own the responsibility of maintenance and repairs and will need to focus on maximising product uptime – since revenue can only be earned when their products are available to generate output in the field. Below, I outline where and how manufacturers will need to use machine learning and predictive analytics, plus how it differs from common instances in consumer- facing markets. Machine learning and predictive analytics in manufacturing The use cases of machine learning and predictive analytics are as varied as the