How to Leverage Edge Computing to Create Easy to Use and Resilient Smart Machines
Q1: What challenges do machine builders face as they work to meet the digitalization, IIoT, and Industry 4.0 requirements of their customers?
A: With the advent of digitalization, IIoT and Industry 4.0, customers are looking for smart machines that complement their smart factory enhancements like securing data collection, empowering the workforce, being able to predict outcomes, preventing downtime, and making the plant more secure. For machine builders, the challenges then become creating products and solutions that provide local control and monitoring at the machine
or process area, integrating multiple disparate siloed solutions, operating under remote and/or hazardous environments, providing operational resilience and downtime prevention, extending HMI/SCADA through remote/mobile device access, running complex applications without the need for IT personnel, connecting to the cloud and enterprise, and deploying advanced applications like MES, AR/VR, and AI/ML.
Create an edge computing based architecture to ensure your solutions operate without disruption from Device, Gateway or Compute Edge to Data Center Control Room and the Cloud.
Q2: How can machine builders meet these challenges?
A: Machine builders should adopt edge computing to solve these challenges. Edge computing is a distributed architecture that brings calculation and data collection closer to the location where it is needed. It is the foundation of digitalization, IIoT and Industry 4.0 solutions and modernizes the architecture of HMI and SCADA that provide local machine monitoring and control. It also includes the collection and storage of large amounts of data from multiple sources, into multiple edge devices that are interconnected all the way up to a global command center and centralized cloud.
Q3: What are the major advantages of incorporating edge into smart machine design?
A: Think simple, protected, and autonomous:
• Simplicity comes through the ability of edge computing to scale, that is, start out small with a single node and grow to multiple platforms as your needs increase. It means having the flexibility to extend the capabilities of monitoring and control beyond the control room or machine control panel using remote mobile devices like cell phones, tablets, and laptops. Another key capability is being able to integrate applications like HMI/SCADA, Historian, MES, AI/ML, and PLC programming that previously required multiple computers into a single device.
• Protected means being able to guard your machines from unplanned shutdown. Edge computing platforms have inherent redundancy that is built into the operating system and performs all critical functions automatically, eliminating unplanned downtime risks. It also comes in Class I Division 2 certified industrial grade configurations so it can be installed in mission critical applications and in hazardous locations. Protected also means enhanced security protects your machines from physical and cyber-security risks. Sponsored by
• The autonomous capabilities of edge computing provide solutions that are self-monitoring, self-protecting and self-synchronizing. This means being able to automatically monitor the health of your edge solution 24x7. It also allows for remotely setting thresholds and receiving alerts, reviewing logs, running predictive failure analysis, and automatically updating and managing patches. It should have an integrated availability layer that automatically improves application resilience. It should have hot swappable nodes that automatically recognize, verify, and synchronize themselves without any human intervention.
Q4: What advanced features do machine builders gain from using edge computing technology?
A: Edge computing platforms can run AI and ML applications. This involves being able to analyze performance and operating data from any piece of equipment, to reliably collect live and historic machine data and detect anomalies in machine operation before downtime occurs. It means being able to employ machine learning and cloud computing to spot quality problems and track KPIs over time. Organizations identify cybersecurity as a critical issue to solve before fully pursuing opportunities at the machine level. This means having edge computing platforms that can address vulnerability and risk, process integrity for critical equipment and data, securely deploy autonomous edge computing platforms, and protect data transmission from edge to enterprise.
Q5:
What is Machine-as-a-Service?
A: Machines are traditionally sold with predetermined specifications based on the customer’s requirements. Machineas-a-service (MaaS) is a business strategy that takes advantage of the capabilities of digitalization to create a machine subscription-based model. If you are a machine builder looking to transform your business into a more service-oriented model, edge computing makes MaaS easier to implement. It is a very flexible solution where factories can be set-up quickly, and the machines are operated and maintained by the machine builders who profit from this service. Implementing MaaS turns a customer’s Capital Expenditure (CAPEX) into an Operating Expense (OPEX). This is a very flexible solution that benefits both machine builder and customer – factories can be set-up quickly, and the machines are operated and maintained by the machine builders who profit from this service: a win-win proposition.
Q6: What should I look for in an effective edge computing platform implementation?
A: Make sure you have an edge computing platform that addresses your machine’s digitalization requirements. Find an operationally resilient platform that can manage local data collection and monitoring and control. Simplify and eliminate silos by leveraging virtualization and integrate multiple applications in a single device. Leverage the advanced edge features like AI and ML to get ahead of your competition.
Resolve all IT/OT Convergence concerns by using a platform that has built-in virtualization and redundancy that can be installed, operated, and maintained by non-IT personnel. Make sure you find a vendor who can help with leveraging service and support as an additional source of revenue.
Establish operational resilience and protect your business from unplanned downtime by leveraging industrial grade platforms bundled with inherent redundancy and security. Eliminate bandwidth and latency issues by installing data collection at the device and gateway edge to connect to control rooms, command centers, the enterprise, and the cloud. Finally, choose an edge computing platform that will provide security protection.