Developing Strong ‘Digital Threads’ To Enable Real-Time Maintenance
One of the biggest value-adds in the industrial IoT space is predictive maintenance, fueled by analytics. Sivakumar “Siva” Muthukrishnan from Manufacturing Business Technology explains why creating digital threads across business operating systems is crucial.
In today’s market, it’s becoming increasingly important to keep the profit margins for equipment competitive, so much so that vendors are relying heavily on service contracts with their customers. However, it gets tricky to balance service contracts on top of the equipment sales as it could lead to customer dissatisfaction and hence lower demand.
Original Equipment Manufacturers (OEMs) sell equipment and receive services revenue from after-sales service contracts. With ever-reducing margins on the equipment sales, services revenue are seen as an attractive business. From an OEM’s business operations standpoint, they need to keep highly skilled maintenance staff and spare inventory with high safety stock to mitigate risk of the end customer’s unplanned stoppages. A slight variation in performance of the machine could lead to quality issues when the end product is produced.
Because of this, real-time insights into equipment and machinery performance are necessary for both OEMs and customers alike, and new technology is helping them predict and manage potential issues. With a smooth flow of information across the supply chain, using technologies like IoT and big data, OEMs and their customers benefit by receiving real-time data collection about their critical equipment parameters, analyzing them using machine learning algorithms and deriving predictive analytics for those equipment and machinery.
With the current advances in technology, we can train data models on similar types of equipment for specific industry and usage patterns, and fine tune it over a period of time. This data is then used holistically along with other data from business operations to create actionable insights and automate actions based on artificial intelligence technologies.
The best strategies companies can implement to manage service contracts, as well as their customer relationships include: (1) developing a digital thread to create a seamless flow of data, and (2) enabling your business processes with IoT capabilities.
(1) – Developing Your “Digital Thread”: This is a thread that creates a seamless flow of data, from conceptualizing a product, to design, manufacturing, installation, repair and disposal, which ties all of these together to increase automation, reduce latency and errors, create new capabilities, and improve performance.
(2) – IoT Enabled Business Processes: It’s important for OEMs to “IoT enable” business process to achieve desired business outcome, as every process step generates information that can be leveraged across the supply chain.
Managing the Risk
With the availability of “Digital Twin” technologies (a virtual model of a process, product or service), it is possible to prove the solution would work in a real-life scenario before building a physical network or infrastructure. Also, one can train the field service personnel on specific equipment or it can be used to simulate a virtual factory.
And what about the infrastructure for IoT? Gartner predicts that 20 billion connected devices will be in use by 2020. The basic thing required for IoT enablement is the ability to identity things uniquely over the network. With the adoption of the IPv6 protocol, we have the capability to identify things uniquely over the internet (2^128 IP addresses).
Therefore, it is possible to uniquely identify connected sensors and devices way beyond 20 billion and for many years to come. With virtually no limitation on connections, every small or large product is set to be manufactured with built-in smart sensors to emit data. Older products, however, will need external sensors to be mounted for specific use. IoT has arrived and is set to grow unbound.
In the current market scenario, there are hundreds of vendors who provide IoT technologies across infrastructure, platform and application architecture layers. Only few vendors provide near end-to-end solutions.
From the IoT value chain, it is quite clear that a very different technology stack is required compared to that of a normal business IT system, and would be viewed as an additional investment for the business. Also, niche skills are required to manage this stack. To overcome these challenges, companies are looking for readily available platform and cloud-based solutions which would do away with initial capital investments and increase time to market.
However, from an OEM perspective, creating and managing the digital thread across business operating systems is crucial. Because of this, it’s beneficial to look for vendors who provide an integrated stack across the IoT value chain with the flexibility to extend, customize and integrate in the context of an OEM’s business.
Vendors focused on developing IoT applications along with Digital Twins, big data platforms, machine learning and mobility, are likely to emerge as the primary choice of technology providers for IoT deployment and stand a good chance to lead the pack.
Without real-time monitoring of machine parameters, quality issues are often only known at the time of inspection of the finished products – by the time considerable production is already underway – hence why it could lead to rejection of the entire batch. Additionally, the cost of quality is very high (specifically in high-price precision items) and in such a scenario, an OEM needs the ability to monitor machine performance in real-time.
Sivakumar “Siva” Muthukrishnan is global alliance manager at Tata Consultancy Services (TCS).
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