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Control, Visibility and IIoT Manufacturing at the Edge (Part 2)

Automating continuous improvement of manufacturing processes and innovation are primary goal of the Industrial Internet of Things (IIoT). A manufacturer’s ability to make production processes smarter through data aggregation may have IIoT at its foundation, but the use of the rugged tablet delivers the connectivity for remote monitoring, management and visualization.

Part one of this blog discussed how cloud-based platforms, edge computing, artificial intelligence (AI) and machine learning (ML) algorithms play a major part in centralized management of manufacturing. When implemented as part of a holistic strategy, these technologies provide the actionable data that fuel established key performance indicators (KPIs).

It’s the KPI metrics that shape data analytics, which in turn is derived from IIoT sensors across countless points in the process or operation of machines that impact quality, uptime, and throughput. An example is how data modeling via digital twins brings potentially hundreds of data streams together to create a digital representation of a single machine or the entire production process. This is one of several major tools making data visibility and control possible at the edge.

Gaining Data Visibility and Control at the Edge

We have learned and manufacturers have experienced that complex applications and analytics are at the heart of automating continuous improvement. Here is where the right rugged tablet becomes the way to monitor, trigger, and intervene in automated processes while in the field – perhaps during inspection and maintenance operations. What many manufacturers are finding is the tablet’s role in automation represents true intervention in the automated process at the edge. The goal is to have access to prescriptive rather than descriptive analytics.

The simple collection and display of sensor data merely describes what is happening in real time. Predictive analytics takes the sum of historical data to make predictions about what things will happen and what things need to happen in the near future. This includes scheduling of events such as predictive and preventive maintenance.

The major goal of edge computing is bringing the data processing closer to where it is being produced by sensors to take potential cloud latency out of the picture. When human analysis and decision-making is required during field operations and maintenance, this requires the chosen rugged tablet to have the compute, storage, and connectivity options that can handle the data aggregation and analytics via onboard applications and compute power. Only a select few rugged tablet manufacturers provide tablet customizations that may enable IIoT field operations, such as physical connection to specialized factory networks, sunlight display readability, or the simple device ruggedness compatible with tough environments such as extreme humidity, dust, potential for liquid immersion, and even explosive atmospheres.

These devices also deliver standard connectivity options (Bluetooth, cellular, Wi-Fi, etc.) to access the internet, the cloud, and close proximity servers for real-time data analytics at the edge. This enables manufacturers to leverage sensor data at a more granular level to predict issues on the shop floor and beyond the network’s edge in the field.

Today’s manufacturers require the power to improve processes and output while lowering downtime through predictive analytics. This level of control can play a major role in end-to-end supply chain visibility as well. There are countless ways that manufacturers can now also use the rugged tablet across the supply chain beyond the network’s edge.

Increasing Supply Chain Visibility for Manufacturing

The supply chain for manufacturing is complex and spread out with countless blind spots that can render production automation less effective. IIoT devices take on a greater role in supply chain monitoring with cloud platforms, edge computing, AI/ML and data analytics providing end-to-end visibility. Systems now have the capability to gather IoT data providing supply chain visibility.

The big problem is the variance of the supply chain environments ranging from warehouses and docks to various modes of intermodal transport. To make all disparate parts of the supply chain visible requires a rugged tablet to ensure it can overcome both environmental, compute and connectivity challenges and provide mobile real time communications with local sensors and edge devices as well as back-end databases and analytics during activities such as inventory management.

Holistic connection between IIoT devices, AI, analytics, and digital twins can provide supply chain modeling that drives prescriptive responses to potential slowdowns and bottlenecks before they occur. It’s not just manufacturing that suffers from lack of visibility. Heavy industry manufacturing, energy sectors, telecom, healthcare and finance all have fluctuations that are unpredictable on the surface to complex supply chains and daily operations. These range from environmental to economic and market forces capable of impacting stability.

Industry 4.0 driven by digital transformation and automation has become the baseline that defines a manufacturer’s ability to compete in 2021 and beyond. IIoT and edge computing are quickly garnering an outsized role in the ability to compete in ways that are redefining the place of rugged tablets. For examples of how SECO can partner with you to create a holistic approach to IIoT control and visibility in manufacturing, follow the link.


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