Karel Kellens

Methodology for systematic analysis and improvement of manufacturing unit process life cycle inventory (UPLCI) CO2PE! initiative (cooperative effort on process emissions in manufacturing). Part 2: case studies

PurposeThis report proposes a life-cycle analysis (LCA)-oriented methodology for systematic inventory analysis of the use phase of manufacturing unit processes providing unit process datasets to be used in life-cycle inventory (LCI) databases and libraries. The methodology has been developed in the framework of the CO2PE! collaborative research programme (CO2PE! 2011a) and comprises two approaches with different levels of detail, respectively referred to as the screening approach and the in-depth approach.MethodsThe screening approach relies on representative, publicly available data and engineering calculations for energy use, material loss, and identification of variables for improvement, while the in-depth approach is subdivided into four modules, including a time study, a power consumption study, a consumables study and an emissions study, in which all relevant process in- and outputs are measured and analysed in detail. The screening approach provides the first insight in the unit process and results in a set of approximate LCI data, which also serve to guide the more detailed and complete in-depth approach leading to more accurate LCI data as well as the identification of potential for energy and resource efficiency improvements of the manufacturing unit process. To ensure optimal reproducibility and applicability, documentation guidelines for data and metadata are included in both approaches. Guidance on definition of functional unit and reference flow as well as on determination of system boundaries specifies the generic goal and scope definition requirements according to ISO 14040 (2006) and ISO 14044 (2006).ResultsThe proposed methodology aims at ensuring solid foundations for the provision of high-quality LCI data for the use phase of manufacturing unit processes. Envisaged usage encompasses the provision of high-quality data for LCA studies of products using these unit process datasets for the manufacturing processes, as well as the in-depth analysis of individual manufacturing unit processes.ConclusionsIn addition, the accruing availability of data for a range of similar machines (same process, different suppliers and machine capacities) will allow the establishment of parametric emission and resource use estimation models for a more streamlined LCA of products including reliable manufacturing process data. Both approaches have already provided useful results in some initial case studies (Kellens et al. 2009; Duflou et al. (Int J Sustain Manufacturing 2:80–98, 2010); Santos et al. (J Clean Prod 19:356–364, 2011); UPLCI 2011; Kellens et al. 2011a) and the use will be illustrated by two case studies in Part 2 of this paper (Kellens et al. 2011b).

Methodology for systematic analysis and improvement of manufacturing unit process life cycle inventory (UPLCI) Part 1: Methodology Description

PurposeThis report proposes a life-cycle analysis (LCA)-oriented methodology for systematic inventory analysis of the use phase of manufacturing unit processes providing unit process datasets to be used in life-cycle inventory (LCI) databases and libraries. The methodology has been developed in the framework of the CO2PE! collaborative research programme (CO2PE! 2011a) and comprises two approaches with different levels of detail, respectively referred to as the screening approach and the in-depth approach.MethodsThe screening approach relies on representative, publicly available data and engineering calculations for energy use, material loss, and identification of variables for improvement, while the in-depth approach is subdivided into four modules, including a time study, a power consumption study, a consumables study and an emissions study, in which all relevant process in- and outputs are measured and analysed in detail. The screening approach provides the first insight in the unit process and results in a set of approximate LCI data, which also serve to guide the more detailed and complete in-depth approach leading to more accurate LCI data as well as the identification of potential for energy and resource efficiency improvements of the manufacturing unit process. To ensure optimal reproducibility and applicability, documentation guidelines for data and metadata are included in both approaches. Guidance on definition of functional unit and reference flow as well as on determination of system boundaries specifies the generic goal and scope definition requirements according to ISO 14040 (2006) and ISO 14044 (2006).ResultsThe proposed methodology aims at ensuring solid foundations for the provision of high-quality LCI data for the use phase of manufacturing unit processes. Envisaged usage encompasses the provision of high-quality data for LCA studies of products using these unit process datasets for the manufacturing processes, as well as the in-depth analysis of individual manufacturing unit processes.ConclusionsIn addition, the accruing availability of data for a range of similar machines (same process, different suppliers and machine capacities) will allow the establishment of parametric emission and resource use estimation models for a more streamlined LCA of products including reliable manufacturing process data. Both approaches have already provided useful results in some initial case studies (Kellens et al. 2009; Duflou et al. (Int J Sustain Manufacturing 2:80–98, 2010); Santos et al. (J Clean Prod 19:356–364, 2011); UPLCI 2011; Kellens et al. 2011a) and the use will be illustrated by two case studies in Part 2 of this paper (Kellens et al. 2011b).

Methodology for systematic analysis and improvement of manufacturing unit process life cycle inventory (UPLCI) Part 2: Case Studies

PurposeThis report presents two case studies, one for both the screening approach and the in-depth approach, demonstrating the application of the life cycle assessment-oriented methodology for systematic inventory analysis of the machine tool use phase of manufacturing unit processes, which has been developed in the framework of the CO2PE! collaborative research programme (CO2PE! 2011) and is described in part 1 of this paper (Kellens et al. 2011).Screening approachThe screening approach, which provides a first insight into the unit process and results in a set of approximate LCI data, relies on representative industrial data and engineering calculations for energy use and material loss. This approach is illustrated by means of a case study of a drilling process.In-depth approachThe in-depth approach, which leads to more accurate LCI data as well as the identification of potential for environmental improvements of the manufacturing unit processes, is subdivided into four modules, including a time study, a power consumption study, a consumables study and an emissions study, in which all relevant process in- and outputs are measured and analysed in detail. The procedure of this approach, together with the proposed CO2PE! template, is illustrated by means of a case study of a laser cutting process.ResultsThe CO2PE! methodology aims to provide high-quality LCI data for the machine tool use phase of manufacturing unit processes, to be used in life cycle inventory databases and libraries, as well as to identify potential for environmental improvement based on the in-depth analysis of individual manufacturing unit processes. Two case studies illustrate the applicability of the methodology.

Environmental impact modeling of selective laser sintering processes

Purpose – This paper aims to present parametric models to estimate the environmental footprint of the selective laser sintering (SLS)’ production phase, covering energy and resource consumption as well as process emissions. Additive manufacturing processes such as (SLS) are often considered to be more sustainable then conventional manufacturing methods. However, quantitative analyses of the environmental impact of these processes are still limited and mainly focus on energy consumption. Design/methodology/approach – The required Life Cycle Inventory data are collected using the CO2PE! – Methodology, including time, power, consumables and emission studies. Multiple linear regression analyses have been applied to investigate the interrelationships between product design features on the one hand and production time (energy and resource consumption) on the other hand. Findings – The proposed parametric process models provide accurate estimations of the environmental footprint of SLS processes based on two des...

Preliminary Environmental Assessment of Electrical Discharge Machining

Manufacturing processes, as used for discrete part manufacturing, are responsible for a substantial part of the environmental impact of products, but are still poorly documented in terms of environmental footprint. This paper presents the first results of a data collection effort, allowing to assess the overall environmental impact of three types of Electrical Discharge Machining (EDM) processes: die sinking EDM, wire EDM and micro EDM. After the inventorisation of all process flows using the CO2PE!-methodology, a subsequent impact assessment analysis allows indentifying the most important contributors to the environmental impact of EDM. Finally some improvement potential is sketched.

Energy related environmental impact reduction opportunities in machine design: case study of a laser cutting machine

Energy consumption is responsible for a substantial part of the environmental impact generated by industrial production (Gutowski et al., 2006). Currently, minimising the energy consumption is hardly a priority for many machine designers, since they concentrate primarily on improving functionality, accuracy and safety. Nevertheless, alternative machine designs with improved energy consumption are emerging. This paper investigates the case of a laser cutting machine as common sheet metal processing machine tool. This paper verifies the potential for energy improvement by means of a case study. The analysis covers both the energy consumption during productive and non-productive time. Energy consumption improvement opportunities are identified. For this purpose a conventional CO2 laser-cutting machine was investigated and compared with a possible fibre laser based machine configuration. The analysis shows that the CO2 laser source and the chiller unit are the largest energy consumers during productive time. During non-productive time, 12% of the yearly energy consumption is required to keep the chiller and other components active. For the alternative machine configuration it is assumed that no energy is needed during off-mode. The same scenario saves 16.6 MWh during productive time because of the improved efficiency of a fibre laser source.

Environmental Analysis of the Air Bending Process

This paper presents the results of a data collection effort, allowing to assess the overall environmental impact of the air bending process using the CO2PE!‐Methodology. First the different modes of the air bending process are investigated, including both productive and non‐productive modes. In particular consumption of electric power is recorded for the different modes. Subsequently, time studies allow determining the importance of productive and nonproductive modes of the involved process. The study demonstrates that the influence of standby losses can be substantial. In addition to life cycle analysis, in depth process analysis also provides insight in achievable environmental impact reducing measures towards machine tool builders and eco‐design recommendations for product developers. The energy consumption of three different machine tool architectures are analysed and compared within this paper.

Environmental Performance of Sheet Metal Working Processes

This paper presents a view on environmental improvement potential of sheet metal working processes at unit process as well as system level. First, results and impact reducing measures for two case studies at unit process level are included. Furthermore impact reduction opportunities at system level are sketched and exergy metrics are briefly discussed.

Environmental Dimensions of Additive Manufacturing: Mapping Application Domains and Their Environmental Implications

Additive manufacturing (AM) proposes a novel paradigm for engineering design and manufacturing, which has profound economic, environmental, and security implications. The design freedom offered by this category of manufacturing processes and its ability to locally print almost each designable object will have important repercussions across society. While AM applications are progressing from rapid prototyping to the production of end-use products, the environmental dimensions and related impacts of these evolving manufacturing processes have yet to be extensively examined. Only limited quantitative data are available on how AM manufactured products compare to conventionally manufactured ones in terms of energy and material consumption, transportation costs, pollution and waste, health and safety issues, as well as other environmental impacts over their full lifetime. Reported research indicates that the specific energy of current AM systems is 1 to 2 orders of magnitude higher compared to that of conventional manufacturing processes. However, only part of the AM process taxonomy is yet documented in terms of its environmental performance, and most life cycle inventory (LCI) efforts mainly focus on energy consumption. From an environmental perspective, AM manufactured parts can be beneficial for very small batches, or in cases where AM-based redesigns offer substantial functional advantages during the product use phase (e.g., lightweight part designs and part remanufacturing). Important pending research questions include the LCI of AM feedstock production, supply-chain consequences, and health and safety issues relating to AM.

Exergy Efficiency Definitions for Manufacturing Processes

The original application of thermodynamic metrics for manufacturing processes has been under development throughout the last decade. The metrics are based on the second law of thermodynamics. Therefore, the exergy value of both input and output streams is used to quantify them. Different definitions of exergy efficiency metric have been employed in previous studies. This difference may hamper its application outside the academic setting. This paper presents comparisons between different definitions for a variety of manufacturing processes. The objectives are to determine the applicability of each definition for specific processes and to demonstrate why more robust definitions still require development.