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VESPER is a visual analytics system for exploring similarity metrics and performance metrics derived from computer-aided design (CAD) repositories. It consists of (1) a data processing module allowing analysts to input custom similarity and performance
Over the past decade, several efforts have characterized manufacturing processes from a sustainability perspective. In addition, frameworks, methodologies, and standards development for characterizing and linking unit manufacturing process (UMP) models to
In the metal cutting industry, power consumption is an important metric in the analysis of energy efficiency since it relates to energy consumption of machine tools. Much of the research has developed predictive models that correlate process planning
Alexander Brodsky, Mohan Krishnamoorthy, Mohomad O. Nachawati, William Z. Bernstein, Daniel A. Menasce
In this paper we report on the development of a software framework and system for composition, optimization and trade-off analysis of manufacturing and contract service networks based on a reusable repository of performance models. Performance models
William Z. Bernstein, Arun Bala Subramaniyan, Alexander Brodsky, Ian C. Garretson, Karl Haapala, Donald E. Libes, Katherine C. Morris, Rong Pan, Vittaldas Prabhu, Arkopaul Sarkar, Arvind Shankar Raman, Zhenhua Wu
The design of manufacturing systems can see dramatic improvements through the use of digital technologies for modeling and simulation prior to deployment. At the 2017 ASME International Manufacturing Science and Engineering Conference held jointly with the
This paper is devoted to studying the performance of multi-product two-machine lines with Bernoulli reliability machines and dedicated finite buffers under priority, cyclic and work-in-process (WIP)-based scheduling policies. For small scale systems, exact
Determining key performance indicators (KPI) is a first step in achieving environmen-tal sustainability of manufacturing operations. KPI selection is a multi-criteria decision making problem, because of various criteria that must be considered. Intuitively
Deverajan Ramanujan, William Z. Bernstein, Senthil K. Chandrasegaran, Karthik Ramani
The rapid rise in technologies for data collection across the entire lifecycle creates an unmatched opportunity to advance the use of data-rich tools for decision-making in lifecycle design. However, the usefulness of these technologies is limited by the
Shaw C. Feng, Wen Su, Xiaolei Xie, Jingshan Lee, Li Zheng
In this paper, an integrated model to minimize energy consumption while maintaining desired productivity in Bernoulli serial lines is introduced. Exact analysis of optimal allocation of production capacity is carried out for small systems, such as three-
Manufacturing organizations are able to accumulate large amounts of plant floor production and environmental data due to advances in data collection, communications technology, and use of standards. Data analytics can help understand and gain insights from
Shaw C. Feng, Deogratias Kibira, Michael P. Brundage, Katherine C. Morris
The need for an open, inclusive, and neutral procedure for developing key performance indicators (KPIs) has been increasing as manufacturers seek to determine what to measure in order to improve environmental sustainability of their products and
Manufacturers are facing an ever-increasing demand for customized products on the one hand and environmentally friendly products on the other. This situation affects both the product and the process life cycles. To guide decision-making across these life
Energy consumption is a major sustainability focus in the metal cutting industry. As a result, process planning is increasingly concerned with reducing energy consumption in machine tools. The relevant literature has been categorized into two research
Gregor Jacob, Christopher U. Brown, M A. Donmez, Stephanie S. Watson
A series of 11 identical laser based powder bed fusion (PBF) builds were completed with varying amounts of virgin and recycled nitrogen gas atomized S17-4 PH stainless steel powder following a specific powder recycling strategy that simulates industrial
William Z. Bernstein, Mahesh Mani, Katherine C. Morris, Kevin W. Lyons, Bjoern J. Johansson
With recent progress in developing more effective models for representing manufacturing processes, this paper presents an approach towards an open web-based repository for storing manufacturing process information. The repository is envisioned to include
Mahesh Mani, Jon Larborn, Bjoern J. Johansson, Kevin W. Lyons, Katherine C. Morris
This paper describes ASTMs new guide for characterizing the environmental aspects of manufacturing processes (ASTM WK35705). The guide defines a generic representation to support structured information. Representations of multiple unit manufacturing
Ian Garretson, Mahesh Mani, Kevin W. Lyons, Swee K. Leong, Karl Haapala
Common terminology is essential for accurate communication between researchers, scientists, engineers, and other decision makers. For manufacturing process characterization, it is imperative for the related terminology to be harmonized to enable efficient
Mahesh Mani, Karl Haapala, Matteo Smullin, KC Morris
The bottom up demand from consumers for more sustainable products, and the top down need to comply with government regulations motivates manufacturers to adopt tools and methods to evaluate their operations for opportunities to reduce environmental impact
Lee J. Richter, Jonathan Downing, Sebastian Engmann, Hyun W. Ro, Andrew A. Herzing, Dean M. DeLongchamp, Subhrangsu Mukherjee, Harald Ade, Maged Addelsamie, Aram Amassian, Yuhang Liu, He Yan
Solution processing via roll-to-roll (R2R) coating promises a low cost, low thermal-budget, sustainable revolution for the production of solar cells. Yet virtually all high performance solution processed research cells have been demonstrated by spin
Bjoern J. Johansson, Mahesh Mani, William Z. Bernstein, Kevin W. Lyons, KC Morris, Laurie Rebouillat, Ilaria Barletta
Efficiency of natural stone production processes in quarries directly affects the economic output and environmental performances, such as production lead times and energy consumptions. Knowledge on stone production processes is crucial in making
This paper proposes a systematic framework using Bayesian networks to integrate all uncertainty sources and available information for uncertainty quantification (UQ) in the prediction of performance of a manufacturing process. Energy consumption, one of
Sudarsan Rachuri, Jinkyoo Park, Kincho Law, Raunak Binge, Mason Chen, David Dornfeld
This paper describes a real-time data collection framework and an adaptive machining learning method for constructing a real-time energy prediction model for a machine tool. To effectively establish the energy consumption pattern of a machine tool over
The future of manufacturing lies in being able to adapt quickly to changing conditions. From smaller lot sizes, to more customization, to sudden changes in supply chain, the variability that manufacturers face is rapidly increasing. The key to enabling