Introducing Smart and Sustainable Manufacturing Systems



A New ASTM Journal

Advanced manufacturing, cyber physical systems, the internet of things, Industrie 4.0…

It goes by many names, but in a newly launched ASTM journal, we call it Smart and Sustainable Manufacturing Systems.

Sustainable manufacturing is basically resource optimization at the system level. These resources include materials, water, capital equipment, and auxiliary units. At its core, sustainable manufacturing is about how “smart” a system is with respect to resources.

This emerging field combines physical systems with big data and intelligence. It has the potential to fundamentally change how products are designed, manufactured, supplied, used, remanufactured, and eventually retired.

A New Forum for Research and Technology

Until now, there has been no unified or common platform for the research and industry communities to publish and exchange ideas. ASTM’s new journal, Smart and Sustainable Manufacturing Systems, or SSMS, fills this gap.

An online publication, SSMS was launched in March with the publication of its first four papers, written by 20 leading minds in this fast-growing field. Access to papers is free during the journal’s inaugural year and can be found at www.astm.org/ssmspapers.

The journal’s editor-in-chief is Sudarsan Rachuri, Ph.D., an internationally renowned expert in smart and sustainable manufacturing technologies (scroll down for more information). More than 50 top global experts serve as the journal’s associate editors, editorial board members, and advisory board members.

For details and to submit papers, click here  or contact Alyssa Conaway (tel: +1.610.832.9620).

Sudarsan Rachuri, Editor-in-Chief, Smart and Sustainable Manufacturing Systems

Sudarsan Rachuri, Ph.D., is the federal program manager for the Clean Energy Manufacturing Initiative’s Innovation Institute on Smart Manufacturing, which was funded up to $70 million through the Advanced Manufacturing Office of the Office of Energy Efficiency and Renewable Energy.

Prior to taking this position, Rachuri spent 20 years at the U.S. National Institute of Standards and Technology, where he initiated several programs, including the Sustainable Manufacturing program and Smart Manufacturing Systems Design and Analysis program.

Rachuri was program manager for the Smart Manufacturing Systems Design and Analysis program from 2013 to 2015. This program addresses research and technology standards issues and explores potential opportunities for dramatically rethinking the manufacturing system life cycle with a focus on assembly-centric production.

In addition to his current work, Rachuri is also working on the High Performance Computing for Manufacturing (HPC4Mfg) program at Lawrence Livermore National Laboratory.

Featured Papers

“An Agent Based Distributed Shop Floor Control System for a Job Shop Environment”
The job shop environment — in which small batches of custom products are made — benefits from the use of decentralized decision support systems. Four authors from the department of mechanical engineering at the Indian Institute of Technology propose a decision-making design that helps answer questions such as “How should intelligence be built into a shop floor agent?” and “How could agents from different domains be integrated?”

“Concept-Based Text Mining Technique for Semantic Classification of Manufacturing Suppliers”
Two researchers from Texas State University propose a way for small- to medium-sized enterprises in the manufacturing sector to remain competitive in the global market by strengthening their web presence.

“Toward a Digital Thread and Data Package for Metals-Additive Manufacturing”
Authors from the Tennessee Technological University and the U.S. National Institute of Standards and Technology present an additive manufacturing information map that leverages informatics to help determine part producibility, process repeatability, and part-to-part reproducibility.

“A Classification Scheme for Smart Manufacturing Systems’ Performance Metrics”
This paper proposes a way to measure the performance of smart manufacturing systems. Ten authors from various academic and research institutions describe how to measure agility, asset utilization, and sustainability using a generalized classification scheme.

May/June
2017
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