Smart Manufacturing Workflow Environment

Establish an initial set of manufacturing process workflow of application (APP) scenarios in cooperation with Smart Manufacturing Leadership Coalition (SMLC) members, NIST, and Department of Energy (DOE) and Department of Defense (DOD) interested participants that will aid in the definition of the requirements for the SMWE architecture.

Identify, Develop, and Document Manufacturing Workflows

Foundational studies of desktop-bound technical computing users, referred to as the “missing-middle” of the High Performance Much has been accomplished to advance the "smartness" of individual machines in manufacturing processes at the micro layer where intelligent sensors, actuators, and process control units implement automated production workflows, however, the identification and application of manufacturing intelligence across a manufacturing plant (the meso layer) and a manufacturing supply chain (the macro layer) languishes. Additionally, with the ever increasing levels of complexity of micro layer components and the increasing volumes of data they produce, there has emerged a “big data” challenge and the need to process the data with high performance computing (HPC) to extract the intelligence required for the higher layers to create a fully integrated smart manufacturing workflow environment. Current solutions are typically proprietary factory-specific one-off solutions with no open design patterns or infrastructure.

An industry-directed group, known as the Smart Manufacturing Leadership Coalition (SMLC), identified that by lowering the implementation barriers around cost, complexity, ease-of-use, and measurement availability, the U.S. manufacturing industry could deploy foundational infrastructure for manufacturing intelligence to collectively strengthen capability. By providing a mechanism for ready access and by lowering the cost and effort to use and support these technologies, small and medium sized manufacturers (SMMs) are incentivized to adopt new manufacturing practices that improve their performance in the form of available easy to use open workflow-based software modules incorporating software applications (APPs) hosted in a cloud platform. Another unique characteristic identified is the notion of bringing the real-time data to the APPs instead of the APPs to the data. Creating an open manufacturing APP workflow cloud platform market ecosystem will also stimulate entrepreneurs to develop and license their IP in the form of models that can be plugged into the open platform.

Nimbis and the University of California Los Angeles (UCLA) with the SMLC as the transition partner, researched the development of the Smart Manufacturing Workflow Environment (SMWE) that will be hosted on the SMLC Smart Manufacturing Platform (SMP) and used by testbed manufactures including Praxiar, General Mills, and General Dynamics. The SMWE will provide an open workflow environment that supports the sequential execution of third party, open source and academic APPs using networked, information based modeling and data analytic technologies, providing the potential to integrate manufacturing intelligence across an entire manufacturing ecosystem. The SMWE leverages Nimbis’ commercial cloud technical analysis marketplace APP hosting infrastructure but now extends it to support multi-dimensional smart manufacturing modeling and real-time data driven process workflows. The workflow architecture orchestrates the use of third party supplied APPs and independent software vendor (ISV) applications providing manufacturing management with alternatives in the right context, at the right time, to the right user to optimize manufacturing plant operations.

SPONSOR / PARTNER
National Institue for Standards & Technology (NIST)

DESCRIPTION
Small Business Innovation Research Project

YEAR
2014

TOPIC
Smart Manufacturing Workflow Environment

SUBTOPIC
Workflow Engine for Smart Manufacturing

PRINCIPAL INVESTIGATOR
Brian Schott

PRINCIPAL-IN-CHARGE
Robert Graybill