The role of the service engineer is changing.
Service engineers have always played a key role within manufacturing operations. If a machine fault occurs or an issue arises which causes production to stop, a service engineer can be called on to identify and fix the problem to get the system back online.
However, this traditional ‘break and fix’ model of service and support can fall short of modern-day manufacturing requirements. Events of the last year have gone to show that demand is unpredictable and that manufacturers must be equipped to continue production no matter what.
This can only be achieved with a fundamental shift from the traditional break and fix model of product support to one of predictive uptime monitoring and proactive quality improvement. A model, as Eddie Storan, Head of Global Service, Domino Printing Sciences (Domino), explains, in which the ‘engineer of the future’ plays a fundamental role.
OEE is everything
Today, manufacturers are placing more importance on maximising uptime by focusing on the overall performance – or overall equipment effectiveness (OEE) – of their production lines. This change in focus can allow manufacturers to react to sudden changes in demand without fear of equipment malfunctioning or breaking down without warning.
The overall output of a production line is inextricably tied to each and every piece of machinery – including coding and marking equipment. It is critically important to ensure that each piece of equipment is running as efficiently as possible in order to reduce the likelihood of an issue arising, which can ultimately put a stop to production.
To take coding and marking as an example, a faulty printer can stand as a barrier to getting products out of the factory door, as codes are typically required for legislative purposes. This is a best case scenario, relying on printer issues being noticed early on – a printer fault which falls under the radar can be a significant cause of production waste, and, potentially, lead to product recalls and hefty fines.
As manufacturers place more emphasis on their OEE, technology providers must be willing to do more than just provide equipment and repair it as quickly and efficiently as possible when a fault occurs. Moving away from the traditional model of product support, technology providers must focus on helping manufacturers to optimise their production lines, to ensure that slight changes in performance are highlighted and fixed before they become a problem.
Connected services and optimisation techniques
In recent years, many organizations have embraced digitization and optimization technologies afforded by Industry 4.0, including automation and cloud connectivity and the addition of sensors (also known as ‘sensorization’), to monitor their manufacturing lines and streamline production processes. This implementation of new technologies provides an opportunity for equipment providers to harness the resulting production data to provide more customized services for manufacturers.
Enhanced production data enabled through the increase of sensorization in production facilities, holds the key to moving from a traditional reactive – or break and fix – approach to the proactive model that forward-thinking manufacturers demand. This model, in which customer data and technical expertise coalesce, is driving the evolution of the role of the service engineer.
Cloud data can be used to observe how a machine is functioning in real-time and identify when a production line is not performing at top capacity. This can allow for the service engineer to proactively alert the manufacturer and intervene before the line fails, minimizing downtime, increasing productivity, and aiding with production planning and supply chain management. If the line in question is a critical line, for example, this would allow the manufacturer to gear up a non-critical line without impacting overall performance.
Augmented reality solutions through the use of connected devices, can allow for remote intervention and assistance. This can include remote installations and service checks, and the provision of remote training where skills gaps have been identified – further enhancing service provision, saving time, and minimizing downtime.
An amalgamation of historical and real-time data can be used to undertake scenario planning and simulation to provide insight into additional value-added services that maximize OEE. This may include identifying areas where new efficiencies can be implemented or building cost models that can identify further areas of productivity improvement.
A trusted advisor
Traditionally, service engineers have played a vital role in getting production lines back up and running after a problem has arisen. However, as manufacturers focus more on the overall efficiency and productivity of their production lines, this is where we will see a fundamental shift in the role of the service engineer.
Beyond the status quo, the engineer of the future will be able to harness insight gleaned from production line data to assume the role of the trusted advisor. This new breed of data-driven service engineer will be able to identify and fix potential problems with machinery before they cause an issue on the line, and, potentially, before a manufacturer even realizes there is a problem. They will help to bridge gaps in customer technical knowledge and offer suggestions for proactive quality improvement to further enhance OEE.
For example, is the line producing the optimal number of units? Is the equipment indicating a higher than-average failure rate? Is the system calibrated to optimize code accuracy? Fundamentally, the engineer of the future will be able to go beyond just making sure the equipment works or ensuring the printer is available, to focus on ensuring that equipment is kept functioning at optimal performance.
To take a recent example where we are beginning to use this type of consultative approach at Domino – a recent review of one customer’s annual service data revealed that, of 22 different issues, 12 had the same root cause of lack of makeup. Having reviewed the data, we consulted with the customer and advised that beacons could be installed to monitor makeup levels and provide an alert to the operator when this should be added. Implementing this simple solution will help to mitigate 60% of the faults moving forward.
Similarly, another annual review highlighted that 70% of a customer’s call outs were not to do with part failure, but with more simple matters around system calibration or wear and tear. By allocating budget, and providing remote training to upskill their operators, the customer now has the capability to resolve these issues directly. These are simple examples of a data-driven outcome-focused approach adopted by Domino engineers to support customers.
New skills
Just as the industry is on a journey, albeit a rapid one, towards digitization, so are today’s service engineers. The engineer of the future will have a varied skill set, including technical knowledge and expertise, as well as face-to-face and remote consultative capabilities and knowledge and understanding of data analytics.
Forward-thinking coding and marking providers are already starting to provide additional training on a wide range of skills and competencies, through the establishment of internal training academies and skills enhancement as an integral part of the job. Crucially, we’re also seeing a change in mindset on the part of the service engineer, from one that is focused on initial training, to one of continuous learning, the specifics of which will be dependent upon the individual solution a manufacturer requires.
We have started to see the rapid evolution of modern production lines, sped up during 2020 by the circumstances imposed by the COVID-19 pandemic. Over the last 12 months, new applications providing virtual customer support and service, and remote training and installations have been rolled out at a rapid speed. Even after the COVID-19 pandemic is over, it is likely that companies will continue to operate in this new digitized world.
In this new environment, the Domino engineer of the future is a form of intellectual capital focusing on data-driven decision making and customer outcomes. They may not attend customer sites as often, and will require a different way of thinking and soft skills in supporting customers. Their technical expertise, combined with the ability to interpret and act upon historical and real-time customer data, will underpin a partnership model that can enable true OEE to minimize waste, optimize performance and profits, and ensure modern production lines are equipped to deal with even the most volatile of circumstances.