By: Kedar Pimplikar, Head of Industrial and Manufacturing, Capgemini October 8, 2024
In today’s business and technology landscape, organizations across industries are being challenged to reimagine their manufacturing and supply chain operations, differentiated product and service offerings and customer experiences to drive innovation, reduce time to market and improve efficiency and productivity. These capabilities disrupt traditional manufacturing approaches and enable new avenues for delivering increased value.
A cornerstone of this growing Intelligent Industry is increased connectivity. The bi-directional digital thread across product design, manufacturing and servicing is gaining more prominence and is enabling industries to visualize ways to make their products, devices and services smarter, better and more connected.
With intelligent operations, the goal is to optimize the entire manufacturing ecosystem to generate products at the desired throughput. As a result of growing competition, there are pressures to meet dynamic demands, optimize energy efficiencies, control waste reductions, minimize unplanned downtimes and achieve higher product quality by the early detection and elimination of production defects.
Industrial connectivity allows manufacturers to monitor real-time information surrounding the overall KPIs on the shop floor. What’s further, new warehouse management systems allow manufacturers to track and trace incoming materials and finished goods, manage logistics seamlessly to optimize supply chain dispatch and assess human intervention on the factory floor to promote safety.
Enabling industrial connectivity
There are many layers of connectivity. In some cases, it can be used to enable IoT technologies for industrial protocols. Beyond smaller tasks, connectivity powers larger devices on a factory network, such as LTE and private 5G networks. Connectivity enables 5G infrastructure on the shop floor and provides a dedicated slice of these high-bandwidth, high throughput networks.
The overall approach to industrial connectivity can be broken down into three broad stages — connect, collate and command.
The connect stage combines foundational operational technologies (OT) and devices with the emergence of network technologies (NT) such as LTE and private 5G networks being deployed on the shop floor. Device connectivity is achieved through inherent local controllers, or add-on modules supporting industrial and industrial IoT protocols. The network technologies are further ‘software defined’ to cater to the custom demands of high-bandwidth, high throughput use-cases at various line levels. An on-demand network facilitates the implementation of more sophisticated technologies, such as wearable devices for connected workers, camera-based systems for safety and quality, as well as augmented robotics, AGVs and similar automation technologies.
The collate stage operates at two levels: industrial edge devices and industrial cloud platforms. Edge devices not only act as a hub to connect to local devices but play a pivotal role in providing manufacturers with decentralized control over the shop floor. Edge applications can be natively supplied by industrial automation providers and further augmented by third party solution providers.
The orchestration of edge devices from the cloud is the true power for enterprises to rapidly scale connectivity. Edge provides localized infrastructure to run AI models — from simple to extremely complex — and regulates the data flow to industrial cloud platforms, for enterprise level consumption.
The command stage enables enterprises to run a Plant Control Tower, which provides visibility on machines, lines and plants efficiency, through KPIs calculation and dashboards. The Plant Control Tower has a variety of manufacturing apps (OEE, predictive quality and maintenance, etc.), complex analytical models, enterprise integrations and dashboards.
Innovative technologies coming to market also have a role to play in this broader industry transformation, specifically artificial intelligence (AI). Data collection and analysis optimized with AI can help leaders identify the root cause of failures, the probability of failures as well as how to increase throughput. Data analytics is fundamental for the ‘what if’ scenarios and can help alleviate uncertainties.
Additionally, AI powers the decentralized control between edge and cloud and enables the use of digital twins to create virtual simulations of the manufacturing facility for initiatives such as scenario planning, virtual commissioning, simulated walkthroughs and training. With digital twins, manufacturers can create a virtual model of their entire operating line to remotely track activities, maintenance and safety.
Long-term sustainability benefits
Beyond the operational, logistical and business benefits, industrial connectivity can play vital role in meeting and exceeding sustainability goals.
There are five key elements that manufacturers should be tracking on the shop floor — water, air, gas, electricity and steam (WAGES). Through the right level of instrumentation, periodic data capture and assessing the ‘unit cost of utility’ at any given throughput, manufacturers can drive the optimal consumption for WAGES.
This connected metering can generate advisories to share alerts about higher consumption patterns, unplanned fluctuations in duty cycles, potential system leakages, better equipment scheduling and more economical energy sources. Real-time access to this data assists in identifying ‘waste hot spots’ across operations and where crucial changes can be made. This will result in enhanced sustainability and operational cost savings, while also serving as effective tool for benchmarking across multiple lines and sites to drive systemic improvements.
Many manufacturers are looking at ways to invest into alternate energy sources and carbon captures, as well as recycling and remanufacturing products. Industrial connectivity will serve as the foundational capability for manufacturers to outperform in this circular economy.
Factors for successful implementation
With any new initiative, there are challenges associated with implementation and adoption. In the case of industrial connectivity, the first major challenge is ensuring that existing machines have a native connectivity mechanism.
Much of the shop floor infrastructure utilized by manufacturers today is legacy machinery that could be decades old and was not designed for inherent connectivity. These machines typically require modifications to add on a connectivity module, which must often follow industrial protocols ensuring the right time sensitivity and latency.
As the machines become connected, the question then becomes how manufacturers can sensitize their analytical models and use the connectivity to pull the required data. During this step, operation teams must determine data parameters, the frequency of data collection and the method for storing data. With access to this data, manufacturers can glean insights into where and how they can optimize their operations across the shop floor.
It can be easy to look at connectivity as it applies to a single machine, but facilities have multiple lines, with several machines operating simultaneously, each potentially with its own unique configurations. Manufacturers must implement a ‘system of systems’ approach to identify and visualize recurring bottleneck issues and optimization opportunities across the entire facility to streamline and improve workflows for higher asset and energy productivity and safer working conditions.
What’s further, change management and talent upskilling is critical focus area when working to implement industrial connectivity. This process involves augmenting new systems, which can include robotics, automated guide vehicles, camera-based systems and beyond to work alongside human operators, thus augmenting human capabilities seamlessly while elevating their roles on the shopfloor.
It is essential for manufacturers to ensure there is synchronization on the shop floor under this new data-driven culture. With the ability to automate unsafe or mundane tasks, mitigate the risks of losing expert know-how from retiring talent and meaningfully attract and engage the next-generation workforce, the role of floor managers will evolve to include more valuable, data-driven tasks. This level of change management will require new training and upskilling to optimize the talent network.
The push for industries to digitize will not slow down anytime soon. As industrial organizations plan for the future, prioritizing smart, connected facilities will be the key to streamlining and optimizing their manufacturing operations.
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