Increasing numbers of companies in the manufacturing industry have identified market potential for implementing sustainable and green manufacturing. Yet, current sustainability assessment tools for companies are complicated, requiring vast amounts of data and technical expertise to use them. Value Stream Mapping (VSM) is founded on lean practices, and it uses a simple method to analyze various types of material, energy, and information flow needed to bring products and services to the end-customer. The objective of this paper is to introduce and illustrate the application of a VSM-based assessment, termed as Sustainable Manufacturing Mapping (SMM). SMM takes chosen sustainability indicators into consideration and is based on VSM, Life Cycle Assessment (LCA), and Discrete Event Simulation (DES). The main phases of SMM include goal definition, identification of the sustainability indicators, and modeling the current and future state process maps. In this paper, some example indicators were identified and an SMM process map was generated for illustrative purposes. 1 3411 978-1-4244-9864-2/10/$26.00 ©2010 IEEE

Manufacturing simulation and digital engineering tools and procedures have had a positive impact on the manufacturing industry. However, to design a sustainable manufacturing system, a multitude of system dimensions must be jointly optimized. This paper proposes an integrated simulation tool helping to maximize production efficiency and balance environmental constraints already in the system design phase. Lean manufacturing, identification and elimination of waste and production losses, and environmental considerations are all needed during development of a sustainable manufacturing system. Engineers designing the manufacturing system need decision support, otherwise sub-optimization is more likely to occur. We present methods for calculating energy efficiency, CO2 emissions and other environmental impacts integrated into factory simulation software.1922 978-1-4244-2708-6/08/$25.00

Discrete event simulation (DES) projects rely heavily on high input data quality. Therefore, the input data management process is very important and, thus, consumes an extensive amount of time. To secure quality and increase rapidity in DES projects, there are well structured methodologies to follow, but a detailed guideline for how to perform the crucial process of handling input data, is missing. This paper presents such a structured methodology, including description of 13 activities and their internal connections. Having this kind of methodology available, our hypothesis is that the structured way to work increases rapidity for input data management and, consequently, also for entire DES projects. The improvement is expected to be larger in companies with low or medium experience in DES.

The rapid development and implementation of digitalization in manufacturing has enormous impact on the environment. It is still unclear whether digitalization has positive or negative environmental impact from applications in manufacturing. Therefore, this study aims to discuss the overall implications of digitalization on environmental sustainability through a literature study, within the scope of manufacturing (product design, production, transportation, and customer service). The analysis and categorization of selected articles resulted in two main findings: (1) Digitalization in manufacturing contributes positively to environmental sustainability by increasing resource and information efficiency as a result of applying Industry 4.0 technologies throughout the product lifecycle; (2) the negative environmental burden of digitalization is primarily due to increased resource and energy use, as well as waste and emissions from manufacturing, use, and disposal of the hardware (the technology lifecycle). Based on these findings, a lifecycle perspective is proposed, considering the environmental impacts from both the product and technology lifecycles. This study identified key implications of digitalization on environmental sustainability in manufacturing to increase awareness of both the positive and negative impacts of digitalization and thereby support decision making to invest in new digital technologies.

In a near future where manufacturing companies are faced with the rapid technological developments of Cyber-Physical Systems (CPS) and Industry 4.0, a need arises to consider how this will affect human operators remaining as a vital and important resource in modern production systems. What will the implications of these orchestrated and ubiquitous technologies in production -a concept we call Cyber-Physical Production Systems (CPPS) -be on the health, learning and operative performance of human workers? This paper makes three main contributions to address the question. First, it synthesizes the diverse literature regarding CPS and social sustainability in production systems. Second, it conceptualizes a holistic framework, the CyFL Matrix, and outlines a guideline to analyze how the functionalities of a CPPS relate to operational and social sustainability-related performance impacts at different levels of analysis. Finally, it presents an industrial use case, which the CyFL Matrix and the related guidelines are applied to. In doing so, the study offers first support to researchers and manager of manufacturing companies willing to define suitable operational and social sustainability-related performances for Humancentric Cyber-Physical Production Systems of the future.