Given the intensely competitive environment facing most sectors, organizations need to be proactively moving forward to avoid unwittingly falling behind. Doing nothing is not an option. This constant need to advance is the driving force behind a broad spectrum of digital transformation initiatives. And any transformation needs to be more than a simple tech refresh; it is why selecting the right technology at the right time is so important.
IoT is and has always been about advancement. Whether it is exploring entirely new business models or evolving existing practices to achieve higher efficiency, IoT looks forwards, not backward.
Manufacturing is an area where IoT can play a particularly important role. IoT is becoming increasingly pivotal in terms of assisting with product development and enhancements. However, it can also deliver significant benefits on the factory floor, safeguarding people, streamlining processes, and fast-tracking production.
Why manufacturing? Why IoT, and why now?
There are many drivers for creating an environment centered on real-time, actionable data. Mobile robotics feed components into the assembly process, condition-based monitoring provides real-time status of mission-critical plant and equipment, and assets – from raw materials to production line personnel – are geo-located to ensure optimum efficiency and safety. A recent study conducted by IMechE, the Institution of Mechanical Engineers, demonstrated just how vital IoT is becoming on the front lines of manufacturing, with almost 75% reporting that understanding advanced data was significant for their business’s future.
The manufacturing sector was an early adopter of analog and proprietary production automation and monitoring systems. But these have their limitations, and, crucially, any data extracted from them tends to be mission-specific and challenging to share across the broader information ecosystem. IoT is the first-choice replacement technology, and monitoring operations or equipment’s performance is already a key goal in more than a quarter of new implementations. IoT has another distinction: its bidirectional nature. While some use-cases focus on commanding action, and others are about collecting specific data points, IoT’s capacity to “close the loop” and apply real-time analytics to data elevates its potential to new levels.
The flexible nature of IoT connectivity is foundational to its value proposition to the manufacturing sector. Previous attempts at transforming the factory floor have met with varying degrees of success. Early systems relied on hardwired connections. While always expensive and time-consuming to implement and prone to damage and degradation, these are increasingly becoming unsatisfactory in environments where cordless flexibility in support of battery-powered electric tooling is now an essential requirement. More recently, solutions have attempted various wireless connectivity technologies: RFID, Bluetooth, Wi-Fi, and Ultra-Wideband. However, these have their downsides in terms of high latency, issues with roaming across the vast spaces typical in manufacturing, and are prone to interference in industrial settings.
However, the latest advancements in Cellular technology are proving to be a game-changer and an excellent enabler for Industrial IoT. It delivers low latency, predictable levels of connection density, and increasingly impressive location-based accuracy. Cellular-connected devices can support a broad range of manufacturing applications. The advantages of Cellular are now so pronounced that some of the world’s largest automobile manufacturers plan to implement private 4G LTE or 5G networks to support their Industry 4.0 evolution. These fully standardized technologies deliver vital capabilities such as secure indoor and outdoor coverage, industrial-grade handover reliability, configurable quality-of-service, mission-critical push-to-talk, and Edge Computing support.
Crucially, 5G Cellular can also deliver throughput levels that satisfy high-bandwidth applications, including provisioning the operating system software for complex-connected products. For example, the modern passenger vehicle ships with more software code than a traditional commercial airliner and downloading Gigabytes of data into each car, as the final production stage is inefficient and prone to bottleneck the line. Additionally, manufacturers are looking to actively interact with elements of the vehicle’s diagnostic systems during the manufacturing process, rather than as a separate quality control step post-build. For this, they need a fit-for-purpose connectivity solution.
It is all about nuance
Connectivity aside, the end-to-end life-cycle management of all of these IoT-enabled manufacturing elements continues to grow in importance. A big part of IoT’s challenge is the rapidly evolving environment in which organizations find themselves. Even the most straightforward IoT project will generally undergo evolution between inception and roll-out. With IoT having long life cycles – five, ten, and even 20 years – it is impossible to predict and mitigate every contingency. Agility and the ability to course-correct is a vital characteristic.
IoT is not a monolithic application, there is no one-size-fits-all technology that satisfies every use-case, and organizations need to embed agility and flexibility into their ecosystem. One of the lessons learned from the first generation of IoT implementations is that success fosters an appetite for expansion. Initial forays into IoT tended to be laser-focused on collecting a single data stream from a set of mission-specific devices, with data applied to a relatively defined business area. There will always be IoT applications with this singular focus and intent. But increasingly, multiple IoT data streams are being aggregated and mined for sharing and integration with the entire enterprise information ecosystem. Manufacturers may well find themselves supporting a mixed bag of IoT solutions, each with potentially quite different requirements, goals, and components. Again, agility and the ability to select the right fit-for-purpose solution on a per use-case basis is a vital capability.
One sure way to ensure service-level agility is to leverage abstraction. Rather than creating intricate designs that rely on tightly coupled interdependencies, each introducing increasing complexity and a degree of stickiness, organizations can insulate themselves by employing middleware that delivers plug-and-play flexibility.
Leveraging its core value of abstraction, Pelion IoT is a platform that seamlessly bridges the physical world of devices and networks to the logic world of data and applications: any device, any network, feeding data to any cloud, and driving any application. Its design ethos incorporates end-to-end security and features standardized interfaces to operational and management systems and applications.
From a customer-perspective, this abstraction translates into the ability to work across chipsets, operating systems, devices types, networks, and system deployments. Abstraction simplifies the solution and implementation, enabling the delivery of trusted data to any choice of application and data management platforms.
Crucially, abstraction streamlines IoT strategies by avoiding premature commitment to still-evolving solution components. Abstraction offers organizations the agility to move between options as technology evolves and as the requirements of a specific IoT use-case demand.
Where to for Manufacturing and IoT
Data shows that manufacturing is a leading proponent of IoT and has demonstrated its commitment by leveraging IoT to help drive strategic and operational decision-making and monitor and optimize performance, products, or internal operations. The Economist Intelligence Unit’s IoT Business Index 2020 report identified the manufacturing sector as second only to IT when implementing IoT for advancing internal processes. Additionally, manufacturers top the list for intentions to increase their IoT investments by up to 50% over the next three years. From tracking assets to provisioning connected products, IoT-empowered systems are quickly becoming essential tools to maximize return on investment and avoid any potential cost of inaction.
IoT has proven itself capable of delivering returns, and perhaps it is the latter that is becoming more of a driver than the former. The potential cost of inaction – the COI – appears to be propelling manufacturers, large and small, to embrace IoT like never before. Recently, ABI Research estimated that a Tier 1 automotive manufacturer could face a $500 million five-year COI. Similarly, a Tier 1 electronics factory could suffer a COI of as much as $650 million. These are big numbers in anyone’s language and get Board-level attention and consideration. Comprehensive management of the IoT estate now comes into its own. Not just in deploying and onboarding, but in establishing and maintaining availability and the credibility and trustworthiness of the data that the IoT solution was purchased to provide. As the manufacturing revectors its processes and practices on IoT-derived data, there is a corresponding rise in the importance of full-featured device management.