You Cannot Have Digital Transformation Without Operational Resilience

Keywords: Digital Transformation, Operational Resilience, Artificial Intelligence, AI, Supply Chain, Sustainability, Cybersecurity, Agility, Reliability, Efficiency

Overview

Manufacturers and processors are all making progress on their digital transformation journeys, deploying smart manufacturing technologies, such as Artificial Intelligence, Analytics, Edge, Cloud, Digital Twin, IT/OT/ET convergence, etc. Despite that, operational challenges caused by geopolitics, tariffs, and increasing weather events, such as hurricanes, floods, tornados, etc. due to climate change, drive manufacturers and processors to leverage tools to ensure the resilience of their operations, especially the integrity of their supply chains. This, combined with challenges caused by the endless barrage of cyber-attacks, and maintaining a productive workforce that is shrinking both in numbers and experience, is drastically impacting the operational practices of manufacturers and processors, driving companies to accelerate their digital transformation journeys from years to weeks in order to respond in real time to these abrupt challenges and become more agile, productive, and operationally resilient, which is the only way that companies can thrive today in a time where the only certainty is uncertainty.

Digital transformation is expediting the ability for physical and organizational boundaries to be broken to engage a real-time workforce, connect teams, and drive collaboration. There are new methodologies and technologies required to increase a company’s operational resilience, driven by the need to monitor, control and protect against failures, ensure product fulfillment and high productivity, protect and upskill personnel, and do all this while leveraging enhanced cybersecurity architectures. To meet these imperatives manufacturers and processors must seek to achieve operational excellence by continuing to accelerate their digital transformation, leveraging a common digital thread from engineering to operations that uses performance intelligence to improve agility, reliability, and efficiency while building operational resilience and sustainability.

Operational Resilience Defined

Operational Resilience is a systematic approach for industrial organizations to ensure best-in-class performance in productivity, quality, and delivery of services and/or products across the manufacturing value network. Operational Resilience spans product design and development; enterprise resource planning and control; supply chain management; manufacturing execution; and operational effectiveness of people, processes, and assets. However, rather than a destination or endpoint, Operational Resilience is an ongoing journey.

Digitally enabled technologies and approaches, such as AI, Industry 4.0, smart manufacturing, edge, cloud, and IIoT have been providing companies with new tools to achieve Operational Resilience. Having a digital thread provides a common denominator for connecting the raw operational and asset data converted into actionable intelligence to all engineering and operational domains that enable humans, software applications, and machines to take the right actions at the right time to continuously ensure operational, asset, and supply chain performance (Operational Resilience is a “moving target”). AI-enabled smart sensors, edge devices, advanced analytics, cloud infrastructure, and digital twins play an increasingly important role here along with additive manufacturing, collaborative robots and AMRs and AGVs, mass customization, and modular manufacturing.

AI and analytics provide an immediate understanding of the current condition of machines and supply chain, helping to predict future performance, avoid issues, and increase operational resilience. They can help predict and avoid mechanical failures, material outages, or other issues that could result in lost profitability and/or unsafe conditions. Process optimization analytics and AI, such as predictive quality, predictive throughput, or predictive energy efficiency, are changing the landscape of efficient operations. In some cases, autonomous automation technology can take the corrective action automatically, freeing people (operators, engineers, maintenance, etc.) to focus on solving problems outside the realm of automation, such as how to increase their company’s operational resilience.
 

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