By Osvaldo A. Bascur, PhD.

Principal Digital Transformation

Imagine if your process manufacturing plants were running so well that your production, safety, environmental, and profitability targets were being met so that your subject matter experts could focus on data-driven business improvements. Through proper use and analysis of your existing operations data, your company can become an industry leader and reward your stakeholders.

Written in an engaging and easily understandable manner, this book demonstrates a step-by-step process of how an organization can effectively utilize technology and make the necessary culture changes in order to achieve operational excellence. You will see how several industry leading companies have used an effective real-time data infrastructure for mission-critical business use cases. The book also addresses challenges involved, such as effectively integrating operational (OT) data with business (IT) systems to enable a more proactive, predictive management model for a fleet of process plants.

The Digital Transformation in the Process Industries book uses a story to discuss how a trilogy of people, business processes, and technologies, centered in data infrastructure, create a successful journey toward a company-wide digital transformation that begins at the local level.

The story begins when Vice President of Operations Bill Roberts hires Peter Argus to lead the company’s operational excellence program. Peter forms an interdisciplinary team (the Digital Transformation Team), who begin reviewing the business processes within the refinery and identifying the white spaces. They find data silos and business functions that are not collaborating as they could. Their data infrastructure system is broken and barely used.

The team focuses on reducing the variance gap between production execution and scheduling. Based on these findings, they develop a smart business template using the latest technologies. They transform data into inFORMation for people, business intelligence, and predictive analytics tools to make sense of the complicated and huge amounts of raw data. They find many hidden quantifiable production and consumable losses.

The results are awakening for management and represent an important business opportunity discovery by the Digital Transformation Team. The team receives permission to implement an enterprise industrial data infrastructure (EIDI) for the company. Through implementation, time, and maintenance costs are reduced company-wide. Management is fully convinced by the tangible results identified that this is a great business opportunity for their survival. They continue on their journey of creating innovative ways to improve business processes, new ways of using data, and giving people the necessary empowerment and skills.

The Book:

  • Emphasizes a culture of sustainable growth and considers how safety and environmental aspects align with profitability and production of products that satisfy customer expectations.
  • Presents how a data infrastructure enables transformation of raw data into operational insights integration with Business Intelligence tools like PowerBI, PI Vision, and predictive analytics tools such as R, Python, and cloud services.
  • Features a Plant Digital Template showing how to digitize operations to transform raw data into operational insights and detect in real time the hidden production losses affecting the plant. It offers examples for developing predictive models to avoid plant excursions, equipment unscheduled downtimes and to improve the running time.
  • Includes examples of companies successfully using operational information to improve yields, soft sensors design and reduce operating costs.
  • Describes buzzwords and translates them into actual examples so engineering professionals and information systems personnel can work together as a team.

Things You Will Take Away:

  • Learn how a real-time data infrastructure enables transformation of raw sensor data into contextualized information for operational insights and business process improvement.
  • Understand how reusing the same operational data for multiple use cases significantly impacts fleet management, profitability, and asset stewardship.
  • See how a simple digital unit template representing production flows can be used repeatedly to identify critical inefficiencies in plant operations.
  • Realize how to transform your organization into a data-drive culture for continuous sustainable improvement.
  • Find out how leading companies integrate operations data with business intelligence and predictive analytics tools in a corporate on-premises or cloud-enabled environment.
  • Learn how industry-leading companies have imaginatively used a real-time data infrastructure to improve yields, reduce cycle times, and slash operating costs.