The service sector is on the cusp of change. New technologies and key trends may affect — and improve — how your facility receives process plant maintenance and other services. Three technologies show promise to optimize service delivery via the use of Industrial Internet of Things (IIoT) technologies.
Predictive Maintenance and Digital Twins
The first way IIoT technologies promise increased efficiency are via so-called digital-twin technologies. One recent report predicts that by 2020, the annual spending on technology for predictive maintenance will reach $10.96 billion — a 38 percent compound annual growth rate over the time frame of 2017 to 2020. These technologies promise to reduce costs, maximize data analytics and extend the lifespan of products.
If an asset breaks down, no longer will the operators need to reactively solicit a service engineer to source and fix the issue. With IIoT sensors, the asset becomes smart, sending data to a central hub that includes diagnostics capabilities. The software will process the data in real time and determine issues that may arise in a day, a week or a month’s time — making a repair job much more efficient.
With the addition of digital-twin technology —digital replicas that represent physical objects in the digital world — manufacturers are able to observe and simulate equipment usage, behavior and performance in the real world via feedback made possible through IIoT. Moreover, with asset feedback available from design to decommission, digital-twin technology enables smarter product design, more efficient service and, ultimately, improved product performance.
The automotive industry has taken this concept on board. For instance, connected cars now send copious amounts of data to be analyzed. Such data is used to engineer better cars going forward as well as alerting when and where faults may start to appear in existing fleets.
Such benefits are not only available to newly engineered products. For those not wanting to heavily invest in new equipment, the good news is IIoT and digital twins can be applied retroactively to legacy products. Sensors placed throughout the physical manufacturing process can collect data relating to environmental conditions, temperatures, pressures, speed and airflow as well as equipment behavior to build a robust digital picture of the process.
Chatbots for Customer Queries
Voice-enabled assistants powered by artificial intelligence (AI) are influencing the way service organizations operate in 2018. Already, nearly four in 10 consumers own in-home assistants, and voice-enabled speakers will be installed in 55 percent of U.S. households by the year 2022, according to research from Juniper Research. Humans are comfortably interacting with chatbots.
One potential industrial process use for chatbots are as assistants to engineers on the plant floor. The voice-enabled assistants would use the data gained from sensors to guide the engineers, says Aydın Fevzi Özçekiç in Chatbots Life. For instance, a voice-activated assistant could remind service engineers of a step-by-step maintenance procedure.
Service presents another potential use for chatbots. Many calls to a service helpdesk are uncomplicated queries and can be answered by a chatbot: There is no need for a live agent to confirm when an engineer is due to arrive. This drives significant potential for companies to connect AI-powered voice assistants to enterprise software, with capabilities such as self-service diagnostics or scheduling optimization engines to automatically offer appointment slots. This can make businesses more effective as well as lighten the load for a stretched contact center agent workforce.
One company that is addressing this market is IBM, which recently launched Watson Assistant, a white-labeled service that runs in the background on the IBM Cloud. I expect this to be a catalyst for the deployment of voice-activated service calls in the coming years. The AI-powered approach is going to become increasingly important in terms of the quality of service received as well as to address growing skills shortages in industry.
The latter is not to be underestimated. In a global IFS Digital Change Survey, 150 decision makers in the service industry rated “recruiting/training/retaining skilled technicians” as the greatest inhibitor to growing service revenue. According to the survey, 28 percent of organizations feel either slightly or totally unprepared to deal with the skills deficit.
AI has the ability to drive improved customer experience, but organizations have some work to do before they can fully reap the benefits. Traditional organizational silos may need to be broken down between engineering, design and service in order to meet the outcome.
Customers Take Control
It is estimated that by 2020, 50 percent of customer services operations will use virtual customer assistants, putting customers in control of operating or servicing their own products. For examples from the consumer world, just think of a Nespresso machine or a Dyson vacuum cleaner. Both companies have invested significant sums in helping consumers — with the aid of a smartphone and a QR code — to access visually overlaid step-by-step instructions on usage and repair. This augmented reality (AR) model, where objects that reside in the real-world are augmented by computer-generated information to create an interactive experience, superimposes digital data to improve the user experience in real-world conditions.
The same kind of model could be applied to more complex systems within an industrial environment, including engines, boilers or even an entire manufacturing line. Strategically positioned QR tags could provide detailed and highly customized plans for users to work from — without superfluous information.
This AR vision shares many of the same benefits as the IIoT, digital twin and AI approaches already mentioned. It will help maximize the time of a limited pool of service engineers, but it also can create a better experience for them. One cannot underestimate the Apple effect here: with AR being built into iOS handsets, it is only a matter of time before the firm democratizes and monetizes such capabilities via an intuitive, user-friendly platform. As well as downloading apps and music, think of downloading an AR experience.
In conclusion, the reality is that AI has plenty of opportunity to drive improved customer experience. However, organizations have some work to do before they can fully reap the benefits. It is important to make a value-based business case for any new approaches. That might mean increasing first-time-fix-rates, offering outcome-based contract types or simply reducing costs by ensuring engineers are only dispatched when strictly necessary.
The AI-powered approach is going to become increasingly important in the context of addressing the growing skills shortages in industry. For instance, a voice-activated assistant could help a service engineer through a step-by-step maintenance procedure.
Traditional organizational silos may need to be broken down between engineering, design and service in order to meet the outcome. An AI-assistant and AR experiences are not miracle solutions: They rely on the engineering data available to populate the systems. It works two ways, though, as the feedback from product sensors will help research and development teams design and build better products going forward.
Ultimately, you need the people, processes, data and systems all optimized to capitalize on these emerging approaches and reap the full benefits for your facility.