Lifecycle Impact Assessment of an Engineering Project Management Process – a SLCA Approach

Dunmade, Israel; Udo, Mfon; Akintayo, T. C.; Oyedepo, Sunday Olayinka; Okokpujie, Imhade P.

doi:10.1088/1757-899x/413/1/012061

Cited by 25 publications

(10 citation statements)

References 18 publications

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“…• Data gathering During S-LCIA stage, an assessment analysis is done by processing the data that are gathered from S-LCI. The social impact on SLCA may impact stakeholder in a positive or negative way [10].…”

Section: Social Life Cycle Assessmentmentioning

confidence: 99%

“…Besides bringing negative impact to the environment, the high production demand in furniture industry also impacts the society. Assessments on social impact are needed to evaluate how a product or process affects workers, costumers, society and the value chain [10]. Among the social impacts related to workers is the decline in worker welfare, which is caused by high production activities.…”

Section: Introductionmentioning

confidence: 99%

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The Improvement of Production Process Impact in Furniture Industry Toward Circular Economy

Wicaksono

Kadafi

2020

E3S Web Conf.

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Furniture industry is the industry that processes raw or semifinished material from wood, rattan, or other natural material, into products with higher value added and benefit. Because of a rise in consumer demand each year, the furniture industries should have much attention. High consumer demand may cause production process-related problems that damage the environment. Such environmental damage may be caused by waste, raw materials, or production process. High consumer demand in furniture industry brings negative impacts not only to the environment but also to the society. Social impact assessment is needed to evaluate how a product or a process influences workers, consumers, citizen, and value chain. This study uses life cycle assessment method with the help of SimaPro software to determine the environmental impact, and social-life cycle assessment to determine the social impact. The largest contributor to environmental impact is the use of acrylic varnish. Substitution acrylic varnish with woodstain-water based aims to lead to a circular economy by reducing adverse impacts on the environment. The replacement of acrylic varnish with woodstain water based reduces the environmental impact score by 24.8%. Social impacts score on the workers and local community stakeholder are categorized as poor.

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Section: Social Life Cycle Assessmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The Improvement of Production Process Impact in Furniture Industry Toward Circular Economy

Wicaksono

Kadafi

2020

E3S Web Conf.

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“…Selection of a preferred method to perform the social impact assessments [4,31,51,59,65] 9 Definition of the system boundaries [13,32,53,57,66,67] 10 Selection of global or location specific data [50,56,59,68] 11 Selection of scoring scales for reporting the results [34,39,50,60,[69][70][71] 12 Selection of stakeholders relevant to the study [39,40,56,57] 4. Discussion…”

Section: Determination Of Challenges From Systematic Mapmentioning

confidence: 99%

Systematic Map of the Social Impact Assessment Field

Bonilla-Alicea

2019

Sustainability

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Social impact assessment (SIA) provides a methodology for defining, monitoring and employing measures to demonstrate the benefits and/or harms created for target communities through evidence of social outcomes and impacts. Although a recent increase in the number of applications is seen, SIA lacks consensus in its methodology, which increases ambiguity and complicates the generalization of any results obtained from individual studies. The objectives of this study are to investigate the methodology of SIA in order to define trends, state of the art, limitations, knowledge gaps, and to recommend future research directions. This study employs a systematic mapping to determine the methods available to perform SIA, and more importantly to identify a set of fundamental challenges faced by practitioners using SIA. Articles are searched through online databases, and are limited to the English language. A total of 81 articles published between 2009 and 2019 were selected, of which 49 included a case study application. A total of 12 fundamental challenges were identified, based upon the screened articles, which serve as a starting point for future research directions to further enhance the SIA methodology.

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“…Nivine et al, [15] used an artificial neural network to predict hourly the house model's indoor temperature made of a hollow cement block. These reviews show that researching thermal analysis of insulation materials is very significant and can increase and maintain the sustainability of the product's economic value [16][17][18][19]. However, this application has not been studied in south-south Nigeria.…”

Section: Introductionmentioning

confidence: 99%

Prediction and Performance Investigation of Polyurethane Foam as Thermal Insulation Material for Roofing Sheet Using Artificial Neural Network

Essien

Bolu

Okokpujie

et al. 2021

ARFMTS

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The prediction and application of Polyurethane Foam in developing roofing sheets cannot be over-emphasized when considering the environmental changes coursed by thermal radiation. This paper presents an artificial neural network application to model and predict the indoor temperature resistance of polyurethane (PU) roofing in residential buildings. The study employed a data logger to measure the indoor and outdoor temperatures for three simulation environments (i.e., morning, afternoon, and evening) for two hours each. Furthermore, the authors employed the Levenberg-Marquardt algorithm to transform and predict the indoor temperature obtained in the residential building's polyurethane roofing house. The result shows that the PU roofing system could absorb the heat and reduce the house model's temperature with 6.9% in the morning, afternoon 15.8%, and 6.8% in the evening when compared with the temperature outdoor environment. The ANN was also able to train, test, and validate the experimental temperature results with 92.86%, 93.92%, and 95%, respectively. The mean square error and a testing error occurs at 0.1707 and 0.1689. Therefore, this study concluded that ANN's application in predicting the thermal insulation material such as the PU roofing system is highly efficient and will increase the manufacturer's performance evaluation. It has also created significant awareness of the community in employing the PU roofing system for residential buildings, which will reduce the rate of energy consumption in buildings.

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Lifecycle Impact Assessment of an Engineering Project Management Process – a SLCA Approach

Cited by 25 publications

References 18 publications

The Improvement of Production Process Impact in Furniture Industry Toward Circular Economy

The Improvement of Production Process Impact in Furniture Industry Toward Circular Economy

Systematic Map of the Social Impact Assessment Field

Prediction and Performance Investigation of Polyurethane Foam as Thermal Insulation Material for Roofing Sheet Using Artificial Neural Network

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