| 1. |
- Johansson, Björn, 1975, et al.
(författare)
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Power Level Sampling of Metal Cutting Machines for Data Representation in Discrete Event Simulation
- 2015
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Ingår i: International Journal of Production Research. - : Informa UK Limited. - 0020-7543 .- 1366-588X. ; 53:23, s. 7060-7070
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Tidskriftsartikel (refereegranskat)abstract
- An extension to the application area for discrete event simulation (DES) has been ongoing since the last decade and focused only on economic aspects to include ecologic sustainability. With this new focus, additional input parameters, such as electrical power consumption of machines, are needed. This paper aim at investigating how NC machine power consumption should be represented in simulation models of factories. The study includes data-sets from three different factories. One factory producing truck engine blocks, one producing brake disc parts for cars and one producing forklift components. The total number of data points analysed are more than 2,45,000, where of over 1,11,000 on busy state for 11 NC machines. The low variability between busy cycles indicates that statistical representations are not adding significant variability. Furthermore, results show that non-value-added activities cause a substantial amount of the total energy consumption, which can be reduced by optimising the production flow using dynamic simulations such as DES.
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| 2. |
- Beheshtinia, Mohammad Ali, et al.
(författare)
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Prioritizing healthcare waste disposal methods considering environmental health using an enhanced multi-criteria decision-making method
- 2023
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Ingår i: Environmental Pollutants and Bioavailability. - : Taylor & Francis Group. - 2639-5932 .- 2639-5940. ; 35:1, s. 250-269
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Tidskriftsartikel (refereegranskat)abstract
- The Healthcare Waste Disposal Method Selection (HCWDMS) is a complicated problem due to multiple and often contradictory criteria with different importance degrees. Thus, decision-makers are restored to multi-criteria decision-making (MCDM) methods to prioritize and select the best HCW disposal methods. This study introduces an enhanced MCDM method to deal with the HCWDMS problem. To address the problem, a comprehensive list of criteria and HCW disposal methods are identified. All the criteria are categorized into four main criteria, and Fuzzy Analysis Hierarchy Process is used to determine the weights of considered criteria and sub-criteria. The study results show that environmental, economic, technical, and social criteria are the most important in selecting disposal methods, respectively. Moreover, the sub-criteria of ‘Health Risk’, ‘Release with health effects’, and ‘Capital cost’ have the highest importance, respectively. Additionally, the methods of ‘Microwave’, ‘Sterilization by autoclave’, and ‘Reverse polymerization’ have the highest priority, respectively.
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| 3. |
- Liu, Yu, et al.
(författare)
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Linking Simulation-Based LCA to Manufacturing Decision Support : An Iron Foundry Case Study
- 2022
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Ingår i: Advances in Manufacturing Technology XXXV. - : IOS Press. - 9781643683300 - 9781643683317 - 9781614994398 ; , s. 325-333
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Konferensbidrag (refereegranskat)abstract
- In recent years, an increasing number of legislations have mandated environmental impact evaluations of products from a life cycle perspective. This study applies a discrete-event simulation-based life cycle assessment to study the environmental consequences that respond to system configuration changes in production processes. The proposed method allows capturing the dynamic links in production processes, which is lacking in conventional static LCA modelling. This approach is demonstrated via a real-world case study of a Swedish foundry production line, where its environmental impacts’ hotspots are identified. These environmental consequences are further analyzed to link to the respective production decision domains for providing suggestions on potential improvements. This study demonstrates the value of combining DES and LCA for revealing the hidden environmental consequences of production processes that are difficult to uncover with traditional LCA studies. Moreover, the strengths and difficulties of the proposed method are also discussed.
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| 4. |
- Liu, Yu, et al.
(författare)
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Review of simulation-based life cycle assessment in manufacturing industry
- 2019
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Ingår i: Production & Manufacturing Research. - : Taylor & Francis. - 2169-3277. ; 7:1, s. 490-502
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Tidskriftsartikel (refereegranskat)abstract
- The manufacturing industry has a duty to minimize its environmental impact, and an increasing body of legislation mandates environmental impact evaluations from a life cycle perspective to prevent burden shift. The manufacturing industry is increasing its use of computer-based simulations to optimize production processes. In recent years, several published studies have combined simulations with life cycle assessments (LCAs) to evaluate and minimize the environmental impact of production activities. Still, current knowledge of simulations conducted for LCAs is rather disjointed. This paper accordingly reviews the literature covering simulation-based LCAs of production processes. The results of the review and cross-comparison of papers are structured in terms of seven elements in line with the ISO standard definition of LCA and report the strengths and limitations of the reviewed studies. © 2019, © 2019 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
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| 5. |
- Beheshtinia, Mohammad Ali, et al.
(författare)
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Identifying and prioritizing marketing strategies for the building energy management systems using a hybrid fuzzy MCDM technique
- 2023
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Ingår i: Energy Science & Engineering. - : John Wiley & Sons. - 2050-0505. ; 11:11, s. 4324-4348
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Tidskriftsartikel (refereegranskat)abstract
- Preventing energy waste in residential and office buildings has emerged as a critical issue in both developed and developing countries over recent decades. The growing demand for oil and energy reserves has amplified the urgency of this concern. The deployment of building energy management systems (BEMSs) can lead to timely responses to changes in environmental conditions, the prevention of energy wastage, a reduction in CO2 emissions, and an increase in the longevity of building equipment. Despite the undeniable benefits of BEMSs, their market size remains small, creating challenges for providers in reaching potential customers. This research seeks to identify and prioritize the marketing strategies for BEMSs. A case study was conducted, employing the “Strengths, Weaknesses, Opportunities, and Threats” analysis as a tool for identifying marketing strategies related to BEMSs. This method resulted in the identification of 18 distinct marketing strategies. These strategies were subsequently prioritized using a novel fuzzy multicriteria decision-making technique, VIkor-topSIS, considering six specific criteria. The findings of the study suggested a hierarchical influence of six criteria on the BEMS market, arranged in the following order of significance: effectiveness, cost, attainability, complexity, timing, and popularity. Furthermore, the top three marketing strategies for BEMSs were found to be internet advertising strategies, discounts to consumers, and online sales. The analysis of the results has also offered valuable insights into the strengths and weaknesses of the studied BEMS provider, as well as the opportunities and threats present within the BEMS market.
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| 6. |
- Beheshtinia, Mohammad Ali, et al.
(författare)
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Evaluating and prioritizing the healthcare waste disposal center locations using a hybrid multi-criteria decision-making method
- 2023
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Ingår i: Scientific Reports. - : Springer Nature. - 2045-2322. ; 13:1
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Tidskriftsartikel (refereegranskat)abstract
- Healthcare waste disposal center location (HCWDCL) impacts the environment and the health of living beings. Different and sometimes contradictory criteria in determining the appropriate site location for disposing of healthcare waste (HCW) complicate the decision-making process. This research presents a hybrid multi-criteria decision-making (MCDM) method, named PROMSIS, to determine the appropriate HCWDCL in a real case. The PROMSIS is the combination of two well-known MCDM methods, namely TOPSIS and PROMETHEE. Moreover, fuzzy theory is used to describe the uncertainties of the problem parameters. To provide a reliable decision on selecting the best HCWDCL, a comprehensive list of criteria is identified through a literature review and experts’ opinions obtained from the case study. In total, 40 criteria are identified and classified into five major criteria, namely economic, environmental, social, technical, and geological. The weight of the considered criteria is determined by the Analytical Hierarchy Process (AHP) method. Then, the score of the alternative HCWDCLs in each considered criterion is obtained. Finally, the candidate locations for disposing of HCWs are ranked by the proposed fuzzy PROMSIS method. The results show that the most important criteria in ranking the alternatives in the studied case are economic, environmental, and social, respectively. Moreover, the sub-criteria of operating cost, transportation cost, and pollution are identified as the most important sub-criteria, respectively.
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| 7. |
- Bhattarai, Prakash C., et al.
(författare)
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Determinants of adolescents’ pro-sustainable behavior : a systematic literature review using PRISMA
- 2024
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Ingår i: Discover Sustainability. - : Springer Nature. - 2662-9984. ; 5:1
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Forskningsöversikt (refereegranskat)abstract
- Climate change is a serious contemporary issue around the world. Adolescents are mostly affected due to climate change. Thus, they are expected to behave in an environmentally appropriate manner, which requires the identification of factors influencing pro-sustainable behavior/pro-environmental behavior. The literature offers a wide range of factors influencing adolescents’ pro-sustainable behavior; nonetheless, these factors are not provided with some common themes. Furthermore, no study integrates dispersed research of the area with a comprehensive systematic review. With this consideration, a systematic review was carried out to find comprehensive factors influencing the pro-sustainable behavior of adolescents. For the review, all 21 interdisciplinary studies on factors influencing adolescents' ecological behavior, published between 2010 and 2023 and indexed in Scopus and Web of Science, were analyzed. The analysis revealed that the number of studies in the area increased after 2020, especially in developed countries, and most studies utilized quantitative research methods. The identified key factors influencing adolescents’ pro-environmental behavior are categorized into demographic, internal, and external factors. The findings can be helpful for future researchers to have rigorous discourse on the issue and expand the research in developing countries using mixed methods research. The policy maker can use findings to motivate adolescents to participate in climate change mitigation.
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| 8. |
- Choudhury, Nanda, et al.
(författare)
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Can machine learning approaches predict green purchase intention? : A study from Indian consumer perspective
- 2024
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Ingår i: Journal of Cleaner Production. - : Elsevier. - 0959-6526 .- 1879-1786. ; 456
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Tidskriftsartikel (refereegranskat)abstract
- This paper explores consumer green consumption practices and considers a set of factors, including cognitive and behavioural level constructs, that influence green consumption. The paper primarily aims to predict the green purchase intention and classify a consumer as a green or non-green consumer. A total of 310 responses were collected and analyzed using machine Learning techniques like Decision Tree, Random Forest, Gradient Boosting, XGBoost, K-Nearest Neighbour, and Support Vector Machine, and the models were validated using different performance metrics. The paper reveals that the main driving factors for a consumer to consider greener options are green self-identification, followed by environmental knowledge, environmental consciousness, and the impact of social media. The current work will allow better product development and the targeting and positioning of green products/services offerings to customers already classified by the system.
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| 9. |
- Despeisse, Mélanie, 1985, et al.
(författare)
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Achieving Circular and Efficient Production Systems : Emerging Challenges from Industrial Cases
- 2021
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Ingår i: Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems. - Cham : Springer. - 1868-4238 .- 1868-422X. - 9783030859091 - 9783030859121 - 9783030859107 ; , s. 523-533
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Konferensbidrag (refereegranskat)abstract
- As the need for more responsible production and consumption grows quickly, so does the interest in the concepts of eco-efficiency and circularity. To make swift progress towards sustainability, solutions must be developed and deployed at scale. It is therefore critical to understand the challenges faced by industry to accelerate the uptake of best practices for circular and efficient production systems. This paper presents the emerging issues from three industrial pilots in an on-going collaborative project. We discuss and suggest further work around crucial questions such as: How to deploy circular solutions from lab to industrial scale? How can digitalization support efficient circular processes?.
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| 10. |
- Flores-García, Erik, et al.
(författare)
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Characterizing Digital Dashboards for Smart Production Logistics
- 2022
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Ingår i: Advances in Production Management Systems. Smart Manufacturing and Logistics Systems: Turning Ideas into Action. - Cham : Springer Nature Switzerland AG. - 9783031164101 - 9783031164118 ; , s. 521-528, s. 521-528
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Konferensbidrag (refereegranskat)abstract
- Developing digital dashboards (DD) that support staff in monitoring, identifying anomalies, and facilitating corrective actions are decisive for achieving the benefits of Smart Production Logistics (SPL). However, existing literature about SPL has not sufficiently investigated the characteristics of DD allowing staff to enhance operational performance. This conceptual study identifies the characteristics of DD in SPL for enhancing operational performance of material handling. The study presents preliminary findings from an ongoing laboratory development, and identifies six characteristics of DD. These include monitoring, analysis, prediction, identification, recommendation, and control. The study discusses the implications of these characteristics when applied to energy consumption, makespan, on-time delivery, and status for material handling. The study proposes the prototype of a DD in a laboratory environment involving Autonomous Mobile Robots.
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