International Journal of Sustainable Manufacturing (9 papers in press)

Special Issue on: Artificial Intelligence and Advanced Data Analytics for Sustainable Manufacturing in Industry 4.0

• Open Access

  Data fusion for improved circularity through higher quality of prediction and increased reliability of inspection ( Free Full-text Access )

  by Robert Schimanek, Pinar Bilge, Franz Dietrich 
  Abstract: In order to meet customer requirements and regulations, such as low carbon footprint, companies are implementing AI-enhanced applications in production. However, AI is often used in stand-alone applications and lacks integration into the overall life cycle of products. To address this gap, this article proposes a framework for improving circularity through data fusion methods in product inspection. Data fusion combines multiple sources of data, like sensor and business data, to improve machine-based predictions. The framework analyses AI applications, prediction during inspection, and data fusion methods, and addresses challenges in integrating business data into predictions. It demonstrates how data fusion improves prediction quality and stability in inspection. The framework is applied and evaluated in a case study from the automotive sector, showing an increase in good-quality predictions based on sensor data, leading to improved resource efficiency and circularity. This framework can be applied to any sector seeking sustainable manufacturing.
  Keywords: data fusion; inspection; artificial intelligence; remanufacturing; circular economy.
  
  
• Sustainability performance of ammonia production: the contribution of Industry 4.0 and renewables to enhance the triple bottom line  
  by Matthew Rumsa, Wahidul Biswas 
  Abstract: A low-carbon transition is underway in the Australian ammonia industry, underpinned by the development of intelligent technologies. A novel framework to assess the sustainability of ammonia production is developed herein by using the triple bottom line (TBL) methodology. As the first TBL study of the ammonia production process, industry and academic professionals are consulted to establish nine weighted performance indicators using survey data. Three scenarios are evaluated, involving increasing levels of automation and Industry 4.0 technologies applied to blue ammonia production. Process data are acquired from literature and a local case study to validate the assessment procedure. An aggregated sustainability index is generated, simultaneously considering a firms environmental, social, and economic performance relative to the increasing technological advances. The resulting analysis determined Scenario 3 as the most sustainable manufacturing process. This suggests further implementation of emerging technologies will continue to yield positive sustainability outcomes for each bottom line.
  Keywords: Western Australia; sustainability assessment framework; ammonia production; Industry 4.0; triple bottom line;.
  
  
• A critical review of industry 4.0 technologies for sustainable manufacturing in remanufacturing development  
  by Jia Yuik Chong, Muhamad Zameri Mat Saman, Safian Sharif 
  Abstract: Remanufacturing is one of the fast-growing industries for sustainable manufacturing (SM) development. However, there is still lack of attention given to Industry 4.0 technologies application, specifically in the remanufacturing industry. This study explicitly performed a content analysis of Industry 4.0 technologies in the remanufacturing context. 36 relevant studies from 2017 to 2021 were selected for critical review. The identified research gaps for future study are: The existing studies only take into account one element of SM, not the three integrated elements of SM in Industry 4.0 technologies on the development of remanufacturing. There is a need to identify the integrated product and process data-driven sharing method to improve the efficiency in remanufacturing operations throughout the supply chain management system. It is suggested that a framework for the implementation of sustainable remanufacturing that incorporates the key elements of Industry 4.0 technology to promote SM advancement toward the circular economy is developed.
  Keywords: remanufacturing; sustainable manufacturing; industry 4.0; technology; smart remanufacturing; circular economy.
  
  
• Automated quality detection of resource-efficient 3-D printing  
  by Purvee Bhatia, Donald McCleeary, Nancy Diaz-Elsayed 
  Abstract: Although additive manufacturing has many advantages including ease of use, flexibility, and waste reduction, maintaining adequate part quality can be challenging. This research proposes to detect production quality characteristics of parts printed via fused deposition modelling using images and machine learning. A Taguchi orthogonal array is used to study the influence of the nozzle temperature, infill density, and feed rate on the surface roughness and energy consumption of the printed parts. Part dimensions and edges are detected by pairing a readily accessible technology (i.e., a smartphone) with advancements in image processing. Adaptive thresholding and the Sobel operator are found to be optimal for edge quality detection. Additionally, the iPhone images were optimal for edge, surface quality, and dimension detection. Surface roughness of the printed parts are predicted using a fine tree machine learning model. The features consisted of infill density, temperature, and feed rate to predict the surface roughness. Infill density and feed rate were positively correlated to energy consumption, while temperature had little effect on energy consumption. Process parameters for 3-D printing are recommended to achieve the desired surface quality, while avoiding print failure and excess energy consumption.
  Keywords: additive manufacturing; sustainability; image processing; energy consumption; 3-D printing.
  
  
• A review of research on smart manufacturing in support of environmental sustainability  
  by Aihua Huang, Matthew J. Triebe, Zhongtian Li, Haiyue Wu, Byung Gun Joung, John W. Sutherland 
  Abstract: Industry 4.0 represents an opportunity to advance the environmental sustainability through interconnectivity, data sharing, and smart machines/production systems/supply chains. Smart machines provide opportunities to improve productivity and efficiency, and reduce the environmental impacts. Sensors applied to the machines provide data to the Internet to predict energy consumption and quantify environmental impact. Data can assist in scheduling to not only improve throughput but to decrease energy consumption for production systems. Tracking and sharing of data across the entire supply chain can also decrease energy wasted through the unnecessary movement. This paper reviews the literature related to Industry 4.0 with attention to advancing smart and sustainable manufacturing. This review considers contributions at i) machines/processes, ii) production systems, and iii) supply chains levels, and examine potential applications and benefits. Finally, this paper concludes with a discussion of challenges and opportunities to achieve smart and sustainable manufacturing and provides suggestions on the future research.
  Keywords: Industry 4.0; smart manufacturing; sustainability; energy efficiency.
  
  

Regular Issues

• Environmental sustainability benchmarking of roof type using life cycle assessment  
  by Asela K. Kulatunga, Raitha Peiris 
  Abstract: At present, alongside the gradual growth of the building construction industry, a massive number of materials have come to be used. Hence, there is a diversity in the impacts caused to the environment by these materials. Consequently, when the product life cycle of a building component (which is constructed by assembling these materials) is considered, its environmental performance is difficult to determine. Likewise, the environmental performance of the entire building component can be evaluated by categorising it into classified scenarios. Considering this need, a scenario-based life cycle assessment (LCA) is generally conducted on roofs, which are one of the main components of a building. One of the major differences between roofs that can be seen is the roof cladding material, and by changing the cladding material, the LCA was conducted repeatedly. The clay cladding roof is compared with commonly available alternatives, such as the PVC roof and the asbestos roof. Clay roof tiles, as a material, could be eco-friendly, but the results of this research study have proven that this is not always the case. The factors that affect this deviation from expectations are further analysed in this research. In addition, a guide is provided on how to recover the depleted eco-sustainability that existed previously in the clay roof tile.
  Keywords: life cycle assessment; environmental sustainability; sustainable manufacturing; roofing materials.
  
  
• Comparison of energy consumption and environmental emissions of diesel engine after-treatment devices based on life cycle assessment  
  by XiaoLei Mei, Tao Li, ShiTong Peng, HongChao Zhang 
  Abstract: Now, after-treatment devices have been proven to affect reducing emissions. However, manufacturing after-treatment devices also produce pollution emissions. This study used a life cycle assessment (LCA) method to evaluate three diesel after-treatment devices: diesel oxidation catalyst (DOC) converter, diesel particulate filter (DPF) and selective catalytic reduction (SCR) converter. The data results show that after-treatment devices have different impacts on the environment, and SCR has more environmental impact. The ozone depletion potential (ODP) pollution is the largest and cannot be ignored. The use of after-treatment devices has great emission reduction benefits, and the quantified reduction rate of environmental indicators exceeds 96%, except for global warming potential (GWP, about 15.26%). An engine equipped with after-treatment devices has some environmental benefits, which are reflected in the five indicators of GWP, AP, EP, POCP and RI, but the use of urea in SCR devices will increase the impact of ODP.
  Keywords: engine after-treatment devices; life cycle assessment; catalytic converter; environmental impact.
  
  
• A TOGAF-based framework for the development of sustainable product-service systems  
  by Kaio Vasconcelos De Oliveira, Ederson Carvalhar Fernandes, Milton Borsato 
  Abstract: Globally, manufacturing companies seek to develop new products and services with less impact on the environment, and consequently better sustainability rates. The impact produced by the COVID-19 pandemic showed that the supply Product-Service Systems (PSS) with an emphasis on sustainability has grown to become one of the main strategic approaches used. The existence of an automated framework capable of assisting designers to create a PSS that encompasses the preparation of products and services simultaneously from its initial stages has become of paramount importance. So the objective of this article is to develop a framework capable of organising the information necessary for the development of product and service in an integrated manner, using the logic of development of information architectures such as TOGAF so that in all stages there is fluidity and there are no duplicity terms in its development. The use of information architecture development methods to develop the PSS structure presents a great opportunity to carry out it's mapping, thus ensuring that the model is adequate to represent real-world situations.
  Keywords: product-service system; TOGAF; automated framework.
  
  

Special Issue on: Circular Economy and Sustainable Manufacturing

• Implementation of Society 5.0 to improve the solar energy sector in the MENA region  
  by Ahmed Abu Hanieh, Afif Akel Hasan 
  Abstract: Solar energy as a renewable resource is used extensively in the Middle East and North Africa (MENA) region for electricity generation and thermal applications. In this paper, adapting Society 5.0 to this sector will be investigated to enhance the implementation of this clean resource in the region. Input and output parameters of the solar energy applications will be integrated with Society 5.0 categories, including modern manufacturing techniques, internet of things, artificial intelligence, big data and mechatronic systems. The developed doughnut model will integrate solar sector, Society 5.0 and sustainable development goals. Many applications are considered for solar energy, including solar water heating using solar collectors, solar photovoltaic panels for electricity generation, food drying, air conditioning and solar cooling. Implementation of the integration between Society 5.0, solar sector and SDGs is demonstrated through solar water heating system.
  Keywords: solar energy system; SDGs; Society 5.0; MENA region; internet of things; artificial intelligence; big data.