Additive manufacturing (AM) is gaining popularity in industrial applications including new product development, functional parts, and tooling. However, due to the differences in AM technologies, processes, and process implementations, functional and geometrical characteristics of manufactured parts can vary dramatically. Planning, especially selecting the appropriate AM process and material requirements can be rather involved. Manufacturability using AM processes has been well studied; however, gaps exist in the design process when catering to the needs of manufacturability. Designers today are challenged with a lack of understanding of AM capabilities, process-related constraints, and their effects on the final product. Challenges are compounded by the ambiguity of where design for AM ends and process planning begins. These ambiguities can be addressed through design principles and corresponding design rules for additively manufacturing parts. The purpose of this paper is to categorically present relevant and reported efforts in design and process planning with design rules in AM. The overarching goal of the review is to offer insights to extract and categorize fundamental principles for derivative rules for different AM processes. Identifying such fundamental requirements could potentially lead to breakthroughs in design and process planning.

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 and improve competitiveness. Manufacturers have actively improved the sustainability of their products through the use of such tools and methods. However recently, manufacturers are struggling to maintain the necessary gains in energy and material efficiency due to the assessment inaccuracies of current ad hoc methods and their inability to identify large sustainability improvement opportunities. Overcoming this barrier requires standardized methods and tools that are implementable and which contain accurate manufacturing process-level information. To aid in developing such methods and tools, this study contrasts the perspective of industry and academic research on the topics of sustainable manufacturing metrics and measurements, and process modeling to determine the deficits that exist in enacting academic theory to practice. Furthermore, this study highlights some of the industry responses to the development of related standards for sustainability assessment.

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 several new use cases in the context of information use in smart manufacturing. This paper examines several key benefits through usage scenarios engaging existing engineering activities. Based on the scenarios, the desired characteristics of an open web-based repository are presented, namely that it will be (1) complementary to existing practices, (2) open and net-centric, (3) able to enforce model consistency, (4) modular (5) extensible, and (5) able to govern contributions. A repository will support and motivate the ubiquitous and extended use of standardized representations of unit manufacturing processes in order to promote consistency of performance assessments across industries and provide a tangible, data-driven perspective for analysis-related activities. Furthermore, the paper presents additional benefits and possible applications that could result from a shared manufacturing repository.

Industrial use of natural resources are increasing at an alarming rate. Engineering and decision support tools are needed for analyzing and curbing industrial consumption of resources. Further, assessment methods to measure and indicate continuous improvement are also needed. Modeling individual manufacturing processes facilitates the generation of quantifiable evidence that improvements are being made. Such a modeling approach is developed and demonstrated in this paper to characterize sustainability performance of two metals inspection processes: magnetic particle inspection for ferromagnetic alloys and penetrant inspection for non-ferromagnetic alloys. Individual unit manufacturing process (UMP) models were developed by observing the inspection practices at an aircraft component manufacturer, and a mathematical basis for comparison with other inspection processes was identified. The paper further demonstrates the aggregation of performance metrics from all UMPs across a manufacturing process flow thus providing a basis for generating detailed sustainability performance assessments of manufactured products. By developing and documenting a comprehensive set of UMP models, more complete knowledge of manufacturing processes can be gained by industry practitioners, leading to continuous improvement of sustainability performance.

Sustainable manufacturing systems use processes, methodologies, and technologies that are energy efficient and environmentally friendly. To create and maintain such systems, well-defined measurement methodologies and corresponding manufacturing information models play a crucial role to consistently compute and evaluate sustainability performance indicators of manufacturing processes that will result in reliable decision support. However, when it comes to describing sustainability of product manufacturing, the presently available methods and tools do not account for manufacturing processes explicitly and hence result in inaccurate and ambiguous decisions between alternate systems. Furthermore, there are no formal methods for acquiring and exchanging sustainability-related information that help establish a consolidated sustainability information base for decision support. This paper presents a study on the scope of the currently available manufacturing information models to incorporate sustainability. Identifying the requirements for information models that cater to sustainable manufacturing was done utilizing an earlier developed Systems Integration for Manufacturing Applications (SIMA) reference architecture model. We propose an extension to the SIMA architecture considering sustainability and refer to it as a GreenSIMA architecture. We present injection-molding unit manufacturing process as an example.

The manufacturing sector accounts for approximately one-third of the total energy consumption in the United States. Today, sustainable manufacturing has become an area of increasing interest, as companies look to reduce their manufacturing footprint and become more environmentally friendly. A science-based methodology, known as sustainability characterization, has the potential for providing companies a way to measure the sustainability of their manufacturing processes. In this paper, the sustainability characterization methodology was used to evaluate the sustainability of die casting unit manufacturing process. More specifically, a way to theoretically model sustainability, based on energy use, was investigated. Using the fundamentals of die casting processes, corresponding input-outputs were first mapped in terms of sustainability parameters and later equations to theoretically calculate the energy used in a die casting machine were identified/formulated. The theoretical energy equations provide a baseline for creating an information model that will eventually lead to creating a science-based methodology standard for sustainability characterization of unit manufacturing processes.

Presently available systems for sustainability assessment do not fully account for aspects related to a product’s manufacturing. In an effort to make more sustainable decisions, today’s industry seeks reliable methods to assess and compare sustainability for manufacturing. As part of the Sustainable Manufacturing program at the National Institute of Standards and Technology (NIST), one of our objectives is to help develop the needed measurement science, standards and methodologies to evaluate and improve sustainability of manufacturing processes. As a first step towards developing standard reference sustainability characterization methodologies for unit manufacturing processes, in this paper we focus on injection molding with energy as the sustainability indicator. We present a science-based guideline to characterize energy consumption for a part manufactured using the injection molding process. Based on the study, we discuss the selection of process parameters and manufacturing resources, determination of cycle time, theoretical minimum energy computations, and estimated energy computations for characterizing the injection molding process.

Manufacturing industries lack the measurement science and the needed information base to measure and effectively compare performance of manufacturing processes, resources and associated services with respect to sustainability. The current use of ad-hoc methods and tools to assess and describe sustainability of manufactured products do not account for manufacturing processes explicitly and hence results in inaccurate and ambiguous comparisons. Further, there are no formal methods for acquiring and exchanging information that help establish a consolidated sustainability information base. Our goal is to develop the needed measurement science and methodology that will enable manufacturers to evaluate sustainability performance of fundamental manufacturing processes ensuring reliable and consistent comparisons. In this paper, we propose and discuss a methodology for sustainability characterization to bridge the measurement science and the needed information base for sustainable manufacturing. This will set the stage for manufacturers to objectively assess and compare different manufacturing processes for sustainability.

Currently available sustainability analysis systems for the die-casting process primarily depend on the material properties and do not account for process information. As a result they are unable to assess or compare the sustainability of parts made using different process plans. In this paper, we propose a new computer-aided system named Sustainability Analyzer for Die-casting Process . Here, we discuss the details of the architecture and the working of the proposed system. We analyze sustainability using three sustainability indicators, namely energy use, solid waste and carbon emissions. The proposed system is verified by comparing results with the actual data measured from the shop floor. The proposed system is beneficial for sustainability analysis comparing different plans alongside material properties, ultimately helping the die-casting industry to reduce carbon emissions and material waste besides improving energy efficiency.

“Sustainability” has become a ubiquitous term in almost every field, especially in engineering design and manufacturing. Recently, an increased awareness of environmental problems and resource depletion has led to an emphasis on environmentally friendly practices. This is especially true in the manufacturing industry where energy consumption and the amount of waste generated can be high. This requires proactive tools to be developed to carefully analyze the cause-effect of current manufacturing practices and to investigate alternative practices. One such approach to sustainable manufacturing is the combined use of Discrete Event Simulation (DES) and Life Cycle Assessment (LCA) to analyze the utilization and processing of manufacturing resources in a factory setting. On an economic aspect such method can significantly reduce the financial and environmental costs by evaluating the system performance before its construction or use. This project considers what-if scenarios in a simplified golf ball factory, using as close to real-world data as possible, to demonstrate DES and LCA’s ability to facilitate decision-making and optimize the manufacturing process. Plastic injection molding, an energy-intensive step in the golf ball manufacturing process, is the focus of the DES model. AutoMod, a 3-D modeling software, was used to build the DES model and AutoStat was used to run the trials and analyze the data. By varying the input parameters such as type and number of injection molding machines and material used, the simulation model can output data indicating the most productive and energy efficient methods. On a more detailed level, the simulations can provide valuable information on bottlenecks or imbalances in the system. Correcting these can allow the factory to be both “greener” and more cost-effective.

Over the past years, institutions in general are increasingly interested and involved in sustainability and social responsibility. In addition, social and political pressures have led to the creation of new regulations and policies that support new business opportunities around global sustainability. Considering sustainable manufacturing, a number of indicators have been proposed and currently being researched. The aim of this paper is to explore and discuss the impact of energy measurements as an indicator for sustainable manufacturing. The main question to be asked is, can energy measurement be used for optimization the machining level process. Based on energy monitoring during two Computer Numerical Control (CNC) machining case studies, the significance of energy cost based on different CNC machining strategies and parameter settings is examined and discussed. The preliminary results from the energy measurements on the case studies indicate that potential cost savings in energy will be minimal in CNC operations. Based on the case studies, the potential energy savings in monetary value do not necessarily justify a company’s investment in implementing real time energy tracking technologies; however the results were limited in scope with regards measuring energy as an indicator for evaluating other performance outcomes.

This paper presents a framework and approach for the computation of machining energy for parts and assemblies, at two levels — early design stage and manufacturing stage. Energy estimation at an early design stage can be useful for redesign strategies and improving manufacturing efficiency. At the manufacturing stage, energy estimations allow for asset management based on energy efficient process planning and scheduling, thereby reducing the negative impacts of the product to the environment. To facilitate the computation of the machining energy, at an early design stage, we first automate the process of identifying the material removal volume for machining operations for a given part. We subsequently use the identified removal volume together with the material specific data to compute an energy range for manufacturing the part. For an assembly, the above computations for individual parts are aggregated to arrive at the final energy range. The proposed method allows the identification of energy intensive parts/features based on the percent contribution, thereby assisting re-design strategies. We additionally explore the application of statistical analysis and allocation principles to identify priority re-design parts. In this paper, we limit our product re-design discussions based on form (geometry and shape) and material. Future extensions will potentially also include manufacturing process optimization. Although the framework presented in this paper is currently applied only to milled parts and assemblies, it can also be extended to other machining methods.

In response to the global trend towards implementing sustainable manufacturing practices, we put forth an exploratory approach that uses energy monitoring as a means to introduce sustainability criteria early into manufacturing process planning. Typically cost, quality and time are the indices for manufacturability assessment in generating manufacturing process plans. In this paper, we propose the idea of introducing sustainability to complement cost, quality and time to arrive at alternative sustainable plans in identified manufacturing processes. To be sustainable, it is pertinent that manufacturing firms understand the energy consumption of different manufacturing equipment used to produce products. This will enable industry to implement energy reduction processes in a more effective manner and pave the way for improved and alternate manufacturing solutions. The paper presents the potential utility of energy usage readings in the interest of continuing dialogue and collaboration.

The need to exchange information between organizations or departments of the same corporation is hampered by interoperability problems that mostly originate from the necessity to comply with diverse standards while using dissimilar applications. Each organization generally uses different standards (both local and international) for products which they produce or use. The differences and similarities of these standards, or gaps and overlaps between these standards create problems when exchanging product information through the product life cycle. Defining gaps and overlaps for these standards will help us better understand the interoperability issues. This will aid in the development of strategies for reducing interoperability problems, thus improving efficient information exchange. In this study, we present different approaches for comparing standards and for identifying gaps and overlaps in standards. A Matrix–based evaluation mechanism developed for this purpose is also described.