A Technology Roadmap by a National Virtual Organization

The world is experiencing trends and events that are having profound implications for the process manufacturing industry in a global economy. The understanding of uncertainty and risk has become fundamental to managing processes and ensuring optimum economic and environmental operation within a safe and responsible operating envelope. Uncertainties in the availability and cost of oil and natural gas, the exponential growth in data storage, communications and information technology, and the relentless pressure of global competition have led to an unprecedented shift toward the business of change, just-in-time processing, high performance cross-disciplinary teams, and the economics of rapid product, operation and management transitions. Sustainability, environment, health and safety have become major areas of performance emphasis.

These are forces that push toward economic and performance metrics of rapid product innovation, proactive situational response, tightly managed product transitions, performance with zero environmental impact and predictive management of production, supply chain, environmental and energy dynamics. The solution to these challenges and opportunities is found in a quantum change in the application and intrinsic assimilation of a model-based, knowledge-enabled environment that addresses a full spectrum of enterprise product, operational and management life cycles. ³Smart Process Manufacturing² (SPM) describes the technology and applied capability in which computationally enabled models are the integrating points for data, expertise, decision and discovery. It is the means of casting data and knowledge into useful forms that can be broadly applied. The knowledge and expertise embodied in SPM need to become key next-generation operating assets and investments so industry can achieve a globally competitive capability.

There is already a trend toward SPM and progress is being made, but needed systemic infrastructural capabilities are yet to be delivered to mobilize a knowledge- and model-enabled process industry environment over the entire product and process life cycle. This report frames the priorities for SPM and articulates an industry-academic consensus on the operating and technological roadmap as well as the priority areas of action for achieving infrastructure capability. Specifically, the focus of this SPM roadmap is on the need for fundamental and broad transformation in thinking and approach. Incremental improvements, while useful, will not achieve the full vision and do not lead to the breakthrough innovation and quantum capability shifts that are needed.

To support, continue and refine the development of the SPM roadmap, we have formed an industry, academic and government Engineering Virtual Organization (EVO) with start-up funding through the National Science Foundation (NSF). The EVO partnership seeks to define the future state of operational excellence, build a consensus around that definition and move toward the fulfillment of the vision.

This report documents the consensus of a national cross-section of industry leaders involved with planning the future of the process industry, vendors that supply technology solutions for manufacturing operations and academic institutions engaged in a range of associated systems research. This report defines Smart Process Manufacturing, establishes the vision and business case and presents a detailed technology and operating roadmap of priority areas of action for transitioning to smart operations.

Several themes in this report were additionally discussed more generally for U.S. industry in a separate but related workshop on Simulation Based Engineering and Science held in April 2009. The specific statements that coincide have been coordinated, integrated and similarly stated in this related but broader report.

Acknowledgment and Disclaimer

These materials are based upon work supported by the National Science Foundation under Grant No. 0742764.

Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.