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Environmental awareness of the effects of single-use plastic packaging and the shortage of non-renewable resources have encouraged the search for alternative materials. Most of single-use plastic p...

The automotive industry has been developed over the years to build lighter and more efficient vehicles; however, the manufacturing processes still have an important environmental impact starting from the acquisition of the raw material until the end of its useful life. In this sense, life cycle engineering contributes to solve the environmental issues produced by the traditional manufacturing industry by considering a process that evaluates the technical aspects of the product but also weights the importance of the environmental impact. However, since there are some alternatives that can be considered as suitable for their technical, environmental, or cost qualities, the multicriteria decision methods used as an engineering tool have been useful to balance all the needed criteria in order to make the best selection. In this sense, this research provided an analysis of five materials that could be used in a rack and pinion system and were submitted to a process of life cycle analysis to consider the environmental parameters as part of the criteria to be assessed by the multicriteria decision methods such as entropy, the Technique of Order Preference Similarity method, the complex proportional assessment method, and the multicriteria optimization and compromise solution, leading to the selection of the best material to be considered for a rack and pinion system. In this sense, the process allowed us to conclude that some materials that are useful can be evaluated by multicriteria decision methods regarding the life cycle analysis, contributing to the application of these methods to make a more environmentally responsible material selection for automotive parts. Furthermore, among all the materials, the best suited for the rack and pinion system was the AISI 4340, which was validated by finite elements simulation, showing that the selection was optimal with a maximum stress of 216.14 MPa, a maximum deformation of 0.0081 mm, and a minimum safety factor of 3.56. In this sense, the simulation validated the selection made before, guaranteeing that the methods used are feasible for automotive applications.

The main intention of the organization is to focused on enhancing its efficiency, life cycle, and productivity by maintaining better delivery time so that customer satisfying can be guaranteed. One way to achieve this intention is by implementing the concept of Total Productive Maintenance (TPM). In this study, barriers faced by Indian manufacturing organizations in the new emerging market had been determined through the questionnaire survey with the help of renowned academician and industrial experts. These barriers had been divided into key areas namely behavioral, organizational, cultural, technological, departmental, operational, and financial barriers. The barriers had positive as well as negative effects on the actual implementation of TPM aligned with life cycle engineering of productive equipment. The study identifies the crucial barriers to TPM employment in Indian manufacturing industries from the literature review and industrial experience. Hence, a unique model was developed for the determination of the driving and dependence power of the barriers to TPM execution to enhance the life cycle of productive equipment using Interpretive Structure Modelling (ISM).

Life cycle engineering (LCE) methods are essential in the development of next generation energy storage systems in order to avoid harmful unintended environmental consequences. Moreover, the integration of life cycle knowledge early in the development stage of such technologies can lead to improved performance in regard to their environmental impact. Extensive information from all stages is needed to understand interdependencies along the life cycle, e.g. between required raw materials, applied processing parameters and lifetime behaviour of the battery. From an LCE perspective, the development of detailed and representative inventories for the assessment of traction batteries is a time and resource intensive process, which requires a difficult synchronization with product development activities. A cyber and physical integration of Life Cycle Technologies in a product system offers the potential to reduce data collection efforts while enhancing its robustness and reliability. Life Cycle Technologies can refer to any product- or process- integrated data acquisition technology, e.g. sensors, which can be leveraged to provide knowledge about a product’s life cycle performance. In this paper, we introduce the concept of Life Cycle Technologies and their potential to maximize the functionality of traction batteries while reducing their life cycle environmental impact. Furthermore, we present a reference architecture aiming at the development and integration of such technologies. Finally, we illustrate its application in a case study of All Solid State Batteries and discuss its usability in the development of new generation battery systems.

Electric stand-up scooters become increasingly popular for both private and shared use. They are a mass product but need to be adapted to different use cases or the local conditions of different cities. However, the sustainability of electric scooters is a matter of public debate, especially because of their short lifetime. Studies show that the reliability of e-scooters is one of the main factors influencing their environmental impact during their life cycle. This paper addresses the research question of the potential advantages and disadvantages of a reliable electric scooter from the perspective of ecological sustainability. It shows how reliability characteristics, especially durability, can affect product sustainability of mass customized products like e-scooters. The paper uses life cycle assessment (LCA) as a methodology. It suggests approaches to include reliability characteristics into LCA and life cycle engineering. Using the three case studies of electric scooters as an example, it outlines the influence of innovation cycles and modular design of batteries, of component durability and scooter lifetime as well as different maintenance strategies on the environmental impact of e-scooter sharing. Altogether the paper discusses possible trade-off between the advantages and disadvantages of improved reliability on the life cycle performance of e-scooters.

This paper presents a vision for a much-needed paradigm shift in Life Cycle Engineering (LCE), which is termed Adaptive and Intelligent Life Cycle Engineering (AI-LCE). To do so, interdisciplinary analysis of literature in domains of AI and LCE is performed. Needed concepts and methods are described: key enabling technologies are Artificial Intelligence (AI), the Internet of Things, and data lakes, which are becoming cost-effective and increasingly implemented in industry. Both artificial and human intelligence are used in combination. Its advantages compared with the conventional LCE include shorter time for changing activities in the lifecycle and the accuracy of changes made.

The appropriate design of product life cycles is crucial for the realization of a sustainable society. Since Alting proposed the concept of life cycle engineering in 1993, many concepts, approaches, methods, and tools have been proposed and developed for the purpose. On the other hand, rapid development of Internet of Things (IoT) technology enables the development, operation, and maintenance of a new generation of products: so-called ‘smart’ products. One characteristic of smart products is the use of data collected throughout the product’s entire life, making it possible to improve energy and resource efficiency. In this context, many efforts have been devoted to developing a variety of algorithms, methodologies, and data models for supporting IoT-enabled engineering activities such as maintenance, production planning, and logistical planning. However, there exists a gap between life cycle engineering and emerging IoT-based technologies; that is to say, little research has addressed the life cycle design of products (including end of life treatment stages) using IoT-based technologies, whereas most IoT-based research focuses on improvement of individual life cycle stages such as production, operation, or maintenance. It is not currently clear how IoT-based technologies can practically contribute to the adequate design of product’s life cycle as a whole. As a first step toward answering this question, this paper proposes a process data model that captures the complex interdependency of product data over multiple life cycle stages. We additionally present a method based on this data model for determining a product’s appropriate life cycle options. Finally, through an illustration of the method with a simplified case study, we discuss the advantages and the future development needs of IoT-based life cycle design.

International conferences such as CIRP LCE usually imply that their attendees travel around the world to reach the venue Several online conferences have already been organised, but the year 2020 was particular because of the COVID-19 pandemics which obliged to cancel or modify dramatically all the events planned from the second quarter of that year The CIRP Life Cycle Engineering conference was no exception and all arrangements made before March were cancelled or modified in order to host the conference online This article presents the environmental impact assessment of the online conference and its comparison to the estimation of the impacts if the event had taken place in Grenoble (France), as initially planned This study confirms that an online conference has lower environmental impacts than a classical conference, except for freshwater quality The main contributors are the country energy mix of the audience for the online conference and the travel by plane for the classical one This article also shows that online conferences might contribute to stay within the planetary boundaries These results encourages to improve the study of the environmental impacts of online conferences and to highlight the hotspots to be improved © 2021 Elsevier B V All rights reserved

Compared with a variety of Design for Environment (DfE) methods (such as design for reduce, reuse, remanufacturing, and recycling), one of the major characteristics of life cycle design is to consider interrelations among the processes across the life cycle stages. In literature, such interrelations have been viewed from flows of materials, products, and energy. To support design and analysis of product life cycles dealing with these flows, engineering tools such as Material Flow Analysis (MFA) and Life Cycle Simulation (LCS) have been studied by scholars in the field of life cycle engineering. However, related works in the field of life cycle engineering mainly focus on flows of physical objects and they do not sufficiently consider information flows in product life cycles. Therefore, the authors have recently developed a simulation framework to design and analyze interactions among constituents of a system with a variety of resolutions (e.g., a process line, a factory, a life cycle) in terms of flows of information and physical objects. The authors develop a recycling system model to be integrated in a life cycle model on the simulation framework. Especially, structural model elements representing facilities used in specific recycling processes (such as separation, sorting, and crashing) are developed based on investigation of specifications of these facilities in market. The facility models are intended to be used for systematically evaluating recycling systems with various combinations of facilities. This paper presents how these facility models are used to structurally and graphically build a recycling system simulation model based on models of interactions among facilities through a case to develop a recycling system of laptop computers.

The aviation industry is increasingly facing the challenge posed by climate change. Alongside the aviation sector, advances in aircraft design and electric propulsion towards sustainability have also emerged in new segments of transportation, the urban air mobility, which has arisen to address the road traffic congestion challenges particularly faced in megacities. Within this new mode of mobility, electric vertical takeoff and landing aircrafts (eVTOLs) have gained interest as a solution for on-demand services, including passenger, cargo transportation, as well as rescue and air ambulances. In this regard, batteries are seen as one of the essential technologies towards decarbonizing the mobility sector. Even though studies have indicated the potential of eVTOLs to enable longer travel distances with significant time savings in comparison with battery electric vehicles (BEVs), the variability in terms of spatial, temporal and technological aspects needs to be addressed in order to assess in how far battery-powered eVTOLs will in fact contribute to a more sustainable urban mobility. Based on a modelling framework of the Life Cycle Engineering (LCE) of future aircraft technologies, this paper investigates the factors contributing to the variability of the environmental assessment results, revealing the inherent complexities of modelling emerging technologies. By simulating different scenarios for the battery operation in eVTOLs and BEVs around the world, a case study demostrates the applicability of the LCE framework in urban and regional application contexts.

Shorter product life cycles and high product variance nowadays require efficient engineering of products and production systems. Hereby a further challenge is that costs over the entire life cycle of the product and production system are defined early in the process. Existing approaches in literature and practice such as simultaneous engineering and design for manufacturing incorporate aspects of production into product engineering. However, these approaches leave potential for increasing efficiency unused because knowledge from past generations of products, production systems, and business models is not stored and reused in a formalized way and future generations are not considered in the respective current engineering process. This article proposes an approach for integrated product and production engineering across generations and life cycles of products and production systems. This includes the consideration of related business models to successfully establish the products on the market as well as the anticipation of future product and production system characteristics. The presented approach can reduce both development and manufacturing costs as well as time to market and opens the vast technological potential for product design to achieve additional customer benefits. Three case studies elaborate on aspects of the proposed approach and present its benefits.

Modelling, analyzing and understanding the life cycle environmental impacts of product systems is, in general, a time demanding and interdisciplinary task. It requires specialized LCA modelling skills and deep knowledge of the product system under analysis. EVs are particularly complex product systems. Their environmental impacts are sensitive to a large set of parameters in the foreground system (FS) as well as to their interaction within specific spatial and temporal contexts and background system (BS).

Electric vehicle (EV) batteries vary from electrode materials, cell packaging to modular configuration. The tradeoffs between their environmental, functional and economical performances are inevitable and essential to achieve the sustainable development of EVs. This study proposed an optimization framework to streamline the modeling processes of eco-design optimization for EV batteries. In this framework, an architecture of life cycle simulation (LCS) model for EV batteries is established to assess the environmental performance of various design schemes. The framework and architecture supply the quantitative environmental insights of the EV batteries and aid in the decision-making of EV battery design. © 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/3.0/ ). Peer-review under responsibility of the scientific committee of the 27th CIRP Life Cycle Engineering (LCE) Conference.

Most surface finishing processes for metals are associated with a high energy demand and the use of chemicals with the potential impact on human- and eco-toxicity. However, surface finishing processes can lead to environmental and economic benefits in other life cycle phases by reducing friction, wear and corrosion. The application of life cycle engineering into surface engineering allows to understand these effects. This study provides a framework to assess environmental and economic effects of surface treatments on other life cycle phases. A case study illustrates the contribution of a surface finishing process for cutting inserts to the life cycle performance.

Faults during machining processes generate negative impacts on productivity, product quality and scrap rate. In recent years, the research of leveraging deep learning algorithms for developing fault diagnostics approaches has been actively conducted. However, the approaches have not been widely adopted by industries yet due to their inadaptability in addressing varying working conditions throughout machining process lifecycles. To overcome the limitation, this paper presents a novel deep transfer learning enabled adaptive diagnostics approach. In the approach, firstly, a Convolutional Neural Network (CNN) is designed to perform diagnostics on machining processes. Then, a transfer learning strategy is incorporated into the CNN to enhance the approach's adaptability for different machining conditions via the following steps: (1) Input datasets from machining conditions are optimally aligned to facilitate cross-domain data reuse; and (2) Weights of the trained CNN are regularized to minimize feature distribution mismatches to implement domain transfer learning. Based on the steps, the CNN can be adaptively applied across the conditions, and thereby re-training processes for the CNN from scratch can be alleviated. The developed approach was validated and benchmarked based on different parameters and settings. In the experiments, comparative results indicate that the approach achieved 94% in accuracy, which was significantly higher than other approaches without transfer learning mechanisms. Peer-review under responsibility of the scientific committee of the 27th CIRP Life Cycle Engineering (LCE) Conference.

It's important to accurately and effectively estimate the overall machining energy consumption so as to compare and select the toolpath that uses the least amount of energy. To this end, a framework to model the energy consumption when machining a workpiece is proposed in this paper. This framework consists of a toolpath planning stage and an energy-modeling stage. The proposed framework is demonstrated using a sample workpiece. The results show that the framework is effective in estimating the machining energy consumption and identifying the optimal toolpath. The framework represents an important method for identifying robust decisions for energy efficiency improvement. © 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/3.0/ ). Peer-review under responsibility of the scientific committee of the 27th CIRP Life Cycle Engineering (LCE) Conference.

Science-Based-Targets are introduced for companies to reduce their greenhouse-gas emissions to stay within planetary boundaries. Climate policies are also introduced to reduce carbon emissions. There may be unintended consequences of such policies that lead to increasing a company's emissions. This is coined as green paradox and may cause carbon leakage, which is not well-addressed in Sectoral-Decarbonization Approach of Science-Based-Targets. This paper introduces an approach to systematically investigate green paradox phenomenon and its impact on achieving Science-Based-Targets by considering economic/environmental consequences of climate policies. The introduced approach allows policymakers to study economic/environmental dimensions of sustainable development in presence of green paradox. © 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/3.0/ ). Peer-review under responsibility of the scientific committee of the 26th CIRP Life Cycle Engineering (LCE) Conference.

This paper introduces the first steps towards a general modelling framework for the integrated life cycle engineering (LCE) of future air transportation systems. The focus of analysis lies on the potential environmental implications of batteries powering electric vertical takeoff and landing aircrafts (eVTOLs), which have emerged as an option for urban air mobility to alleviate automobile traffic in cities. The impact of main influencing factors on the sustainability of eVTOLs is discussed, presenting the main modelling requirements for an LCE framework to accompany the transition towards a more sustainable air mobility.

Agricultural food production systems are essential to face current and future climate, food security and nutrition challenges. Several novel urban agriculture production concepts are utilizing symbiotic production and distributed/urban production principles to address these challenges. Life cycle engineering can support the planning and design of production systems and help to identify hotspots and avoid problem shifting. In this work the authors identify the factors resulting from symbiotic, distributed and enclosed food production, influencing life cycle inventory modelling for life cycle assessment. Based on the influencing factors a life cycle inventory modelling framework is proposed and the application pathway is illustrated by an in-development production system called CUBES Circle.

The application of Life Cycle Engineering methodologies during the development of frontier and emerging technologies, such as batteries, is essential to anticipate unexpected problem shifting when mitigating current sustainability challenges. As development of such technologies is often framed in multidisciplinary research contexts, structured knowledge management of all relevant information is required. This paper introduces the concept of Knowledge Based Life Cycle Engineering to structure and link multidisciplinary knowledge, enabling a collaborative system modeling and life cycle analysis. We present the components that comprise the approach: knowledge engineering, repository and data platform; along with an implementation based on a reference ontology.

The virtual reality technology (VR) has undergone a rapid development in recent years. The VR software and hardware have become powerful and affordable. Therefore, the VR counts to the key technologies for enabling the digital transformation. However, this significant technology has not achieved the expected breakthrough in the industrial engineering area yet. The potential of the VR to digitize and to improve the engineering process of industrial companies especially for SMEs is still undiscovered. This has led to a poor implementation and use of the VR applications with an engineering scope compared with other business sectors e.g. gaming, entertainments. This paper presents and discusses two case studies achieved within cooperation project between the University of Applied Sciences Karlsruhe and German manufacturers for fire trucks and systems for firefighting and disaster protection. The aim of the case studies is the implementation of VR applications and their evaluation in terms of using in the business processes of the involved industrial partner. Based on the experiences gathered during this cooperation project a CAD Data transformation process for an industrial VR application as best-practice approach will be outlined and discussed in this paper. © 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/3.0/ ). Peer-review under responsibility of the scientific committee of the 27th CIRP Life Cycle Engineering (LCE) Conference.

Plastic waste is internationally recognized as a problem, fueled by increased public awareness of environmental concerns and the steady increase in waste import bans. Modern sorting and recycling technologies are mature, but face implementation limitations in highly dense urbanized regions such as Singapore due to significant space constraints and expensive labor. Distributed plastic sorting and recycling facilities at small-scale closer to points of plastic waste generation offer the possibility of increasing the recovery of plastic waste streams in urbanized settings. To quantify the environmental performance of such systems, this study compares the life cycle greenhouse gas emissions of large-scale centralized facilities versus distributed small-scale facilities for sorting and recycling plastic bottles and takeaway containers generated in the central region of Singapore. An agent-based model is used to simulate different scenarios of plastic waste generation, collection routes, sorting, and recycling. The simulation results are used in a multi-level life cycle assessment to quantify the greenhouse gas emissions of the plastic sorting and recycling network as well as its individual entities. The results reveal that the life cycle greenhouse gas emissions of small-scale distributed plastic recycling compared to large-scale centralized systems are sensitive to the transport distance traveled and the type of trucks used. © 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/3.0/ ). Peer-review under responsibility of the scientific committee of the 27th CIRP Life Cycle Engineering (LCE) Conference.

The main objective of this paper is to develop a model that will combine economic and environmental assessment tools to support the composite material selection of aircraft structures in the early phases of design and application of the tool for an aircraft elevator. An integrated life cycle cost (LCC) and life cycle assessment (LCA) methodology was used as part of the sustainable design approach for the laminate stacking sequence design. The model considered is the aircraft structure made of carbon fiber reinforce plastic prepreg and processed via hand layup-autoclave process which is the preferred method for the aircraft industry. The model was applied to a cargo aircraft elevator case study by comparing six different laminate configurations and two different carbon fiber prepreg materials across aircraft’s entire life cycle. The results show, in line with other studies using different methodologies (e.g., life cycle engineering, or LCE), that the combination of LCA with LCC is a worthwhile approach for comparing the different laminate configurations in terms of cost and environmental impact to support composite laminate stacking design by providing the best trade-off between cost and environment. Elevator LCC reduces 19% by changing the material type and applying different ply orientations. Elevator LCA score reduces 53% by selecting the optimum instead of best technical solution that minimizes the displacement. Improving the structural performance does not always lead to an increase in the cost.

Existing tools for educating undergraduate students about sustainable engineering methods are notably lacking. In particular, these tools are unable to support the assessment of competing objectives in the evaluation of economic, environmental, and social performance across the lifecycle during product design. In an effort to address this deficiency, an interactive, web-based learning environment, a distributed cyberlearning environment, Constructionism in Learning: Sustainable Life Cycle Engineering (CooL:SLiCE) has been created. CooL:SLiCE aims to facilitate the consideration of different human controlled/initiated impacts on the natural environment through personalized individual and team-based design activities. Thus, CooL:SLiCE enables constructionist (physical, hands-on) learning in engineering via a virtual platform that allows students to visualize/analyze the effect of changes to product designs, manufacturing processes, and supply chain configurations on sustainability performance. The overall conceptual framework of the CooL:SLiCE platform is discussed. Additionally, the application of constructionism as a pedagogical approach for sustainable engineering education is presented. The framework is designed to facilitate attainment of deeper conceptual understanding in environmentally responsible product design and manufacturing by supplying a set of tools that support a constructivist learning environment. This tool set is based on disparate methodologies from the design, industrial, and manufacturing engineering domains. A team project was undertaken to pilot the CooL:SLiCE platform to aid design and assessment during the sustainable product development process. The pilot project demonstrated the capacity of the CooL:SLiCE platform in the understanding of sustainable product design concepts. This research advances the current educational tools for sustainable product design by integrating three learning modules into a web-based environment developed in the CooL:SLiCE project to provide a platform for learning not currently accessible to engineering educators and students. Future work will mainly focus on using the platform in the classroom settings to investigate its effect on improving student understanding of sustainable life cycle engineering.

For techniques used to estimate battery state of charge (SOC) based on equivalent electric circuit models (ECMs), the battery equivalent model parameters are affected by factors such as SOC, temperature, battery aging, leading to SOC estimation error. Therefore, it is necessary to accurately identify these parameters. Updating battery model parameters constantly also known as online parameter identification can effectively solve this issue. In this paper, we propose a novel strategy based on the sunflower optimization algorithm (SFO) to identify battery model parameters and predict the output voltage in real-time. The identification accuracy has been confirmed using empirical data obtained from CALCE battery group (the center for advanced life cycle engineering) performed on the Samsung (INR 18650 20R) battery cell under one electric vehicle (EV) cycle protocol named dynamic stress test. Comparative analysis of SFO and AFRRLS (adaptive forgetting factor of recursive least squares) is carried out to prove the efficiency of the proposed algorithm. Results show that the calibrated model using SFO has superiority compared with AFFRLS algorithm to simulate the dynamic voltage behavior of a lithium-ion battery in EV application.

International audience; Targeting sustainability in our industrial society requires integrating specific criteria in the design process of products and processes. A paradigm shift is necessary in the economical, social and political systems to ensure the natural ecosystems preservation on the planet while fulfilling society needs. Various research methods have therefore emerged to change the way products and services are designed, developed, used and discarded considering territorial contexts. Design for Sustainability, Design for Sustainable Transition, Socially Responsible Design, post-growth design, etc. provide several methods integrating the sustainable principles in the design process. However those approaches remain mainly experimental and are limited to the industrial context. In parallel to those approaches a wide variety of grassroots initiatives have emerged in territories. They propose alternative ways to design systems and they integrate new constraints in a practical manner. This research therefore aims to confront the diversity of Design to Environment (DtE) approaches with 'grassroots' initiatives in order to understand the possible evolution of the integration of sustainability into the design process of products and services used in industry. This paper presents the first literature review results of a started project in 2020. An original research protocol is proposed in this paper, based on specific focus groups with grassroots initiatives practitioners and eco-design experts from research and industry. The presentation of four DtE frameworks are analysed in this paper. This research finally discusses the opportunity of integrating the grassroots enriched DtE frameworks by non-officialdesigners in life cycle engineering. This bottom-up process may drive an expression of sustainability in industry aligned with some emerging local socio-technical systems.