Syncron UptimeTM accelerates manufacturers’ transition from after-sales service to Products-as-a-Service (PaaS)

SyncronTM today announced the launch of Syncron UptimeTM, a new solution offering that uses Machine Learning and Artificial Intelligence to efficiently analyse real-time sensor data, predict failures, prescribe optimised maintenance actions and ultimately maximise product uptime.

Servitisation, which is the transformation from selling products to selling products-as-a-service, has ushered in a new generation of customers that prefers access over ownership. This increasingly popular consumption preference is driving original equipment manufacturers (OEMs) to shift from product-centric to service-centric business models.

“While servitisation will enable OEMs to create more customer value and reduce cost, it will also require many to redefine the way they operate and serve their customers,” said Henrik Lenerius, Chief Product Officer at Syncron. “OEMs not only need to optimise their traditional, break-fix after-sales service operations, but also future-proof their businesses to meet the customers’ evolving consumption preferences. Subscribers expect their equipment to be up and running at all times – putting previously unseen demands on manufacturers’ service organisations. The launch of Syncron Uptime, coupled with increasing data-transfer bandwidths (5G), IoT, AI and Machine Learning, is paving the way for OEMs to facilitate predictive and prescriptive maintenance, optimise productivity and maximise product uptime more efficiently than ever before.”

 

When implementing an after-sales service strategy that is centred on maximised product uptime, OEMs commonly encounter the following challenges:

  • Failure patterns: A small minority of the overall mechanical failures that contribute to unplanned downtime follow a pattern that is correlated to time and/or usage, while the overwhelming majority are random occurrences. As a result, today’s approach to preventative maintenance adds to increased total cost of ownership without effectively improving availability and uptime. The only way to improve product uptime and cost effectiveness without increasing risk is to look for subtle symptoms and pre-cursors leading up to the point of failure.
  • Data: To overcome random, symptom-based failures, OEMs have been investing heavily in sensors and IoT, collecting massive amounts of data. However, it is impossible to manually manage or analyse this data in any beneficial way. The only solution is to leverage modern Machine Learning and AI technologies – mathematical algorithms that can find the subtle patterns to provide the earliest possible indications of anomalies and failure patterns.
  • Complexity and knowledge management: Today’s manufacturers are focused on designing products that are easier and safer to operate. However, this has led to increased complexity when it comes to servicing and maintaining newer equipment. Simultaneously, the baby boomer generation is retiring and taking critical, expert knowledge with them, leaving OEMs struggling to find trained service technicians and engineers who can effectively troubleshoot and diagnose problems based on early symptoms, which can lead to a reduction in first-time fix rates.
  • Organisational siloes: Manufacturers’ organisational structures are designed for today’s product-centric approach, treating sales of products, spare parts and service as separate functions. This has led to disparate IT systems, KPIs and more. Servitisation, however, requires a new way of thinking where accountability does not end after a product sale, but instead continues throughout a product’s entire lifecycle. OEMs will be contract-bound for pre-defined performance measures that carry incentives and penalties based on customer outcomes.

 

Syncron Uptime has been specifically designed to overcome these challenges, enabling OEMs to maximise product uptime cost effectively. Specific benefits of this new, enterprise software solution include:

  • Combining OEMs’ investments in IoT and sensor data with sophisticated Machine Learning and AI technologies to detect anomalies and predict failures, leading to optimised maintenance for every complex machine in the field and ultimately improving product uptime and maintenance costs.
  • Capturing knowledge and best practices for troubleshooting products with the earliest and smallest indications of deterioration in performance, increasing field service productivity and improving first-time fix rates.
  • Breaking down data and organisational siloes to enable coordination between operations, field service management and service parts planning, providing a single source of truth to all stakeholders.
  • Integrating predictive maintenance work requests with field service systems and Computerised Maintenance Management System (CMMS) to make the best decisions for both the business and end customers, while maximising product uptime and improving the overall customer experience.

 

Lenerius continued, “This is a pivotal moment in time for manufacturers as they increasingly focus on maximising product uptime and making new business models work. Technology will accelerate the journey to servitisation and Syncron provides the solutions that evolve and scale alongside manufacturers as their needs change and mature over time. We are thrilled to launch Syncron Uptime and look forward to continuing to enable the world’s most sophisticated manufacturers in this transformation.”

To join the elite group of manufacturers that are part of the Syncron Uptime early adopters programme, please visit syncron.com/uptime.

 

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