Five in 5: Manufacturing optimization for process industries

1. How would you describe integrated operations for process manufacturing?

Dr. Ramesh Vaidhyanathan: Integrated operations is the unification of the end-to-end operations value chain from planning and scheduling to production execution and shipping in a closed loop, converging the supply chain and manufacturing operations. Integrated operations go beyond providing real-time visibility and alerting—to analyzing, predicting, making insightful decisions, and collaboratively responding to adverse events across business and operations functions to transform operations performance. Unplanned disturbances in any part of the value chain (such as production downtime, slowdowns, and shipping delays) can have adverse impacts upstream and downstream—which can lead to suboptimal asset utilization, reduced revenue and margins, and increased costs. By connecting the value chain, companies can be better informed and prepared to deal with these changes.

Harpreet Kaur: Siloed and outdated systems are impacting chemical manufacturers’ ability to obtain visibility across supply chains and operations—creating unintentional silos. This can lead to a delayed response to deviations, operational inefficiencies, and increased costs. What if companies could integrate and process information in manufacturing operations—using the latest technological advances, such as artificial intelligence (AI), for improved collaboration, proactive predictions, and AI-optimized decision-making? This is the essence of integrated operations. It helps companies drive “execution as planned” to realize the full potential of operational assets.

2. What are the key challenges around integrating different operational functions for process manufacturing?

Dr. Ramesh Vaidhyanathan: The challenges in integrating different functions in the value chain can be viewed from the people, process, and technology perspective. First, the roles, responsibilities, and requirements of key stakeholders (such as planners, schedulers, operations supervisors, operators, supply chain managers, and inventory and shipping managers) must be clearly defined. Then, the integrated business processes on how these personas interact and collaborate to resolve adverse operational events in a closed-loop fashion need to be developed. Finally, the siloed systems and data should be integrated to provide end-to-end visibility with context, enabled by event-based intelligent workflows and automation with advanced analytics and AI advisory capabilities.

Harpreet Kaur: For me, the biggest challenge to overcome is integrating data and providing information visibility across functions. Historically, processes were set up and optimized in silos, but now through digital technology, there’s an opportunity to do end-to-end digitalization. For example, if supply chain and inventory managers have visibility into operational issues and shipping challenges, they’d be able to make decisions that optimize inventory levels across the value chain—avoiding any increases in shipping and inventory holding costs. In many cases, planners are still planning based on historical data and a finite set of planning scenarios, which is suboptimal when reacting to unplanned events. In today’s world, it’s no longer sufficient to optimize in silos. We must look to end-to-end processes across the value chain.

3. Why should companies consider pursuing integrated operations? What are the values and potential benefits?

Dr. Ramesh Vaidhyanathan: Chemicals and materials manufacturers are facing challenges with reduced margins and profitability stemming from operational disruptions across the value chain. Integrated operations can enable collaborative problem-solving and efficient operations, leading to improved product revenues and reduced operational costs.

Even for companies with mature planning optimization capabilities, a significant portion of the optimal planned value could be lost due to an inability to respond to adverse events dynamically and proactively across business functions. Integrated operations enable companies to realize the optimal potential of their assets. An example would be lost revenue due to underutilized assets and inefficient production and logistics, which can lead to missed production or shipping targets. In addition, the inability to respond to value chain disruptions in real time can lead to increased logistics, shipping, and demurrage costs. Integrated operations will likely increase productivity and help ensure optimal execution of plans to drive better asset utilization, revenue realization, and lower costs.

Harpreet Kaur: In addition to the tangible benefits outlined by Ramesh, I believe it also sets up the right foundation for a culture of innovation and data-driven decision-making. As the energy and chemicals industry gears up for disruptions and readjustments due to energy transition, companies must constantly innovate. Aggregating information and data across functions is the first step in providing the necessary foundation for innovation. Better real-time visibility and optimization can drive up to a 20% increase in revenues, reduction in costs, and improved customer satisfaction. It’s also beneficial in attracting the digital-native workforce, especially younger employees who value information and innovation.

4. What does the future of truly integrated operations look like?

Dr. Ramesh Vaidhyanathan: The future of integrated operations will be enabled by digital, remote operations and autonomous capabilities. AI will help to monitor, control, and ensure that autonomous plant operations are as per the optimal plan to meet production, inventory, and shipping. We’ll likely have self-healing operations that can respond to disturbances based on learning and intelligent workflows.

Autonomous and integrated operations will likely be augmented by connected workers, assets, and expertise to supervise and intervene as needed. A remotely connected and distributed workforce will help troubleshoot issues, simulate scenarios, resolve problems, and push optimal solutions to the autonomous plant guided by AI. The connected workforce will utilize immersive augmented reality (AR) and virtual reality (VR) technologies, robotics, and drones to perform remote operations and asset management, improving safety and productivity.

Harpreet Kaur: It’s an interesting question. The ultimate goal is to automate operations and processes in manufacturing, but what’s going to be interesting (and yet to be seen) is the path companies take to implement different digital tools to enable that vision. The technology is maturing, but it’s equally important for the client’s organization and culture to enable this vision. It’s not a small change, and ultimately, this requires companies to think and behave differently. How can organizations prepare the workforce as operations get more interconnected and automated? How can companies keep data secure and still leverage state-of-the-art AI tools for automation?

5. How can process manufacturing companies get there?

Dr. Ramesh Vaidhyanathan: The core of integrated operations is the convergence of operational technology (OT) and information technology (IT) systems and data with context, the ability to predict and detect events, gain insights, make intelligent decisions, and respond. The foundational capabilities required for integrated operations are the same as those of smart manufacturing and industry 4.0 transformation. On top of this, integrated operations add the framework for intelligent workflows, robotic process automation, and AI learning capabilities.

The integrated operations journey needs to start with the overall future-state vision, strategy, and road map to achieve objectives. This will be further enabled by a future-state architecture built on top of and integrated with the existing systems landscape. It’s imperative that integrated operations connect to existing OT/Internet of Things (IoT) and IT source systems to leverage the data and events. This can be achieved through standard open-source protocols such as open platform communications (OPC), message queuing telemetry transport (MQTT), and via application programming interfaces (APIs). Leveraging this converged data, predictive analytics data science models and AI learning-based advisory capabilities can be developed and deployed using artificial intelligence for operations (AIOps).

Harpreet Kaur: To get to the target state, companies need to carefully curate a series of “coordinated” choices across four pillars: process, technology, data, and humans. They have to identify which processes to integrate or optimize to drive business cases while evaluating the technology architecture and data choices that come with it. It’s easier said than done—there’s a need to adopt a portfolio approach of applications that are part of a cohesive architecture, which evolves through agile development of digital capabilities. Driving behavior change in humans can’t be an afterthought. Trust will be a key factor. The organizational readiness approach needs to combine a deep understanding of human complexity in the operations environment with high-resolution behavioral data. Another important criterion is to keep a forward radar to cope with the increasing pace of disruptive technologies and decide where, what, when, and how to adopt them for program goals.

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