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Company-wide manufacturing networks have grown complex, connecting a broad range of devices from laptops to factory machines. This has led to increased reliance on automation and artificial intelligence and machine learning (AI/ML) to simplify operations. Automation replaces manual tasks, reducing labor costs, and enhancing production speed. For instance, analytics helps in implementing predictive maintenance solutions. IoT sensors in machines collect real-time data for predictive maintenance and optimal schedules. They also monitor inventory levels, assisting in maintaining optimal stock, reducing waste, and preventing interruptions due to shortages.
However, to successfully implement both automation and analytics, it is essential to have a network that is agile, flexible, and ubiquitous.
IT has conventionally been about setting up and managing infrastructure in response to business needs, with a primary focus on controlling the costs of infrastructure.
However, with the emergence of as-a-service consumption, IT departments in manufacturing have a chance to alter this dynamic. The cost structure of as-a-service technology, coupled with the capacity to scale services based on results and to seamlessly incorporate new capabilities, helps transition IT efforts from merely reducing costs to activities that meaningfully contribute to profit generation.
The rapid increase of remotely accessed devices, assets, and sensors in factories, warehouses, vehicles, and offices is adding complexity to manufacturing organizations. These organizations view IoT as a potential solution to a myriad of problems, ranging from predictive maintenance on machines, product quality control, to energy efficiency. Also, manufacturers can enhance employee safety by monitoring air quality in various environments and track warehouse efficiency by observing the movement of assets and equipment.
However, such an influx of devices on the network will necessitate a deeper convergence between IT and operational technology (OT) teams. Given that OT relies heavily on the network, both IT and OT teams will need to work together and share information on network and device health, frequency band usage, security, policy, and maintenance efforts. To do this effectively, IT will require a more data-driven and mobile network.
The complexity of mobility, a heterogeneous device base, and IoT means IT is thinking differently about security. IT teams in manufacturing environments have recognized that security cannot be a guarded perimeter around the network and instead needs to be pervasive through the network, as cyberattacks can disrupt production processes, compromise sensitive data, and cause financial losses. A study by IBM found that the average cost of a data breach for manufacturing companies is $4.45 million. From every location to every device, from the in-plant office to the connected security camera, security must permeate everything in the network.
Network access is available 24 hours a day, seven days a week, globally. Network operations teams need to be able to react to security threats at any point in the day or night, wherever they are. Immediate network access, whether an admin is on-premises or at home, is imperative.
Each of these trends plays into one another, creating a renewed need for simplicity, resiliency, and agility in how network operations teams manage the network. This is ultimately driving manufacturing IT toward cloud management for the network, with three in five enterprises already reporting the use of some level of cloud-based platform to manage network infrastructure.
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