Zero downtime is the dream of any field service business. Having technology back in action without dispatching a technician is perhaps an extension of that dream, and having the technician wrap up a work order with minimal mean time to repair (MTTR) is the closest that this dream gets to reality.

In my previous article, I discussed how high-performance teams such as the Red Bull Racing Formula One team ensure quick turnaround (or minimal MTTR), but there are two key concepts that manufacturers and engineers could use to raise the bar—even for field service providers. Failure Modes and Effects Analysis (FMEA), which provides a systematic approach for diagnosing service failure, and Design for Serviceability (DfS), which is a modular approach to system design aimed to facilitate maintenance and repairs, are two tactics that engineers and field service techs can use to speed up and improve how they provide support to customers. 

FMEA Takes a Proactive Approach to Service

FMEA has been used quite effectively to improve reliability in product design, business process design, and asset maintenance, and it lends itself equally well to field services. FMEA works by engineers and service providers identifying “failure modes,” or the ways in which a product, service, or process could potentially fail. A project team thoroughly examines every element of a service, starting from the inputs and working through to the output that’s actually delivered to the customer. At each step, the team asks, “What could go wrong here?” and assigns the answer a risk priority number (RPN). 

The RPN, which is a metric used to drive FS-FMEA measures, is the product of the Severity (S) of a failure occurring in field; Occurrence (O), which is the chance of such failure happening; and Detection (D), which is the chance of such a failure being detected. The goal of the scoring system is to focus improvement efforts on the errors that may potentially have the biggest impact on customers and identify ways to detect the problem and develop recommended actions.

By being more proactive about potential service challenges that may arise in the field before they occur, service technicians will be better prepared to not only identify the problems, but also resolve them quickly, thereby reducing MTTR.

DfS Simplifies Design to Streamline Service

At its core, DfS refers to the modification (namely simplification) of a product design in an effort to make its servicing easier and quicker. A few common examples of such design modifications include reducing the number of fasteners, optimizing the overall number of tools required for assembly and disassembly, replacing Allen screws or cheese head screws with the easier-to-use thumb screws, and eliminating fasteners in difficult-to-access locations.

Field service technician feedback is an important component of DfS, so using a field service application that enables easy data and feedback capture in the field is critical. Plugging in employee suggestions not only gives technicians a sense of ownership in product design changes, but also improves design with their unique on-the-scene insight. 

For both FMEA and DfS, however, one of the biggest obstacles is that more often than not, the knowledge about many of these failure modes and design aspects are dispersed throughout the organization in various systems or silos (commonly referred to as tribal knowledge). The key to being a world class organization lies in making this knowledge systemic, accessible to all, and usable for design and manufacturing decision-making. Failure to achieve this means missed opportunities to prevent potential service mishaps, which means downtime and lost profits. Just as Lew Platt, former CEO of Hewlett-Packard, said, “If HP knew what HP knows, it would be three times more profitable.”

About Anil Pai

Anil PaiAnil Pai is the global head of TCS Digital Field Service Management Practice, which is focussed on providing solutions and services to field service organizations. He has more than 25 years of business experience across multiple roles, industry verticals and countries, including India, Germany and Australia.

Anil is a mechanical engineer by qualification and his experience includes roles in methods engineering, industrial engineering, supply chain and inventory management, production planning and execution, lean manufacturing, and consulting and management for ERP transformations. Anil worked with European multinational corporations Robert Bosch and ABB before joining TCS in 2008. Prior to taking up his current assignment in 2018, he led TCS SAP Practice for Australia and New Zealand, operating from Sydney.

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