Optimization of process operations in the leather industry

Adopting pollution prevention strategies (PPS) can ensure environmental sustainability (ES) in the leather industry and can help the industry achieve several sustainable development goals (SDGs). In order to ensure the ES of the leather industry, there is a need for research to identify a comprehensive list of PPS. This research aims at identifying the most effective PPS for the leather industry, which are categorized into 4R (reduce, reuse, recycle, and recover) dimensions. This is a case study where four leather processing companies from Bangladesh were purposively selected. Through an extensive literature review and experts’ opinions, 21 PPS are identified for the leather industry’s ES. Also, this study shows several benefits of PPS through which various SDGs can be achieved in the leather industry. This study will certainly guide the leather industry managers to ensure the ES of the leather industry and, consequently, assist in achieving several SDGs.

Nonsmooth differential-algebraic equations in chemical engineering

Leather industry has commonly been associated with high pollution due to the bad smell, organic wastes and high water consumption caused during traditional manufacturing processes. Different forms of waste in quality and quantity, which emerge during the transformation of hides and skins into leathers in thousands of leather factories, from primitive to modern all around the world, have negative impacts on the environment. In leather factories solid waste containing protein that constitute more than 60% of raw hide weight are disposed to the environment without turning them into good use at industrial level. A biological approach such as alkaline protease production by different microorganism is prominent way to utilization of tannery proteinaceous solid waste. In this research work four different species Bacillus licheniformis, Bacillus coagulans, Bacillus polymxa and Bacillus amyloliquefaciens were isolated from soil sample and identified by biochemical tests. These species efficiently produce alkaline using animal fleshing (ANFL) which is an untanned tannery solid waste as prominent source of protein .The efficiency of protease production was measured on different temperature, pressure and incubation time. Bacillus licheniformis gave highest protease production. Due to efficient production of alkaline protease by same bacillus species, it can be use at industrial level.

The integration of advanced machine learning (ML) and artificial intelligence (AI) techniques in the oil and gas industry is rapidly evolving, focusing on improving operational predictions and optimizations. This study investigates the frequency and interconnectedness of key terms associated with these technologies through network diagrams and academic research results. An extensive search in the Scopus database revealed significant trends and patterns, highlighting the central role of forecasting and optimization within the industry. The interdisciplinary nature of the research underscores the need for collaboration across various fields to tackle complex challenges. While data quality and infrastructure pose challenges, the potential for enhanced efficiency, reduced costs, and increased safety through AI and ML applications is substantial. Case studies demonstrate the practical benefits, and future advancements promise deeper integration of these technologies into industry operations.

This chapter reviews a number of case studies across the different states in India. It includes textile, pharmaceuticals, and paints industry from West Bengal; textile and dye industry in Rajasthan and Tamil Nadu; sugar industry in Maharashtra; pulp and paper industry in northern India; and tannery industry in Uttar Pradesh and Tamil Nadu. From these case studies, we find that different industries have adopted different measures depending on their capacity. These case studies provide further insight regarding the implementation of common effluent treatment plant (CETP) and effluent treatment plant (ETP). The findings from the West Bengal studies reveal that measures to control water pollutants by setting up ETP in five industries have been successful. While the experiences from leather industry in North and South India show similar results where both have used CETP to control water pollution, a typical cluster of pulp and paper industry in Northern India shows the feasibility of ETP compared to that of CETP. In general, the performance of CETPs has been found to be very unsatisfactory largely because of poor operation and maintenance.

Energy optimization of an FPSO operating in the Brazilian Pre-salt region

Framework for a smart data analytics platform towards process monitoring and alarm management

The leather industry is a traditional industrial sector. The industry uses both a high variety and high amount of chemicals during the production of leather from raw hides and skins. The chemicals used will end up in the product, in the environment (wastewater, solid waste, air) and in by-products. This chapter describes how a modern tannery in Sweden is working with the risk management of chemicals in order to reduce the health and safety risks at the company and also to reduce the environmental impact of the company and avoiding hazardous chemicals in the product. The tannery is using 350 different chemicals in the different processes and in general the tannery adds 3 kg of chemicals for every kilogram of leather that is produced. The tannery has implemented environmental management systems and has a very good control of all processes in the tannery. The chapter focuses on how the tannery assesses new chemicals before they are introduced, how the tannery substitutes potential dangerous chemicals by less dangerous alternatives, how the tannery reduces the impact of chemicals to the environment by the use of best available techniques complemented by treatment facilities such as a newly built wastewater treatment plant and finally how the company monitors the content of certain chemicals in the finished leather.

The leather industry has gained high socioeconomic relevance in India and contributes significantly to the economy and export growth. Nearly 2000 tanneries operate throughout India, with a total processing capacity of 700,000 t/y of raw hides or skins. In the present study, co-digestion experiments were carried out using fleshings (a tannery process solid waste) along with the primary and secondary sludge generated during treatment of tannery wastewater. The significance of optimization of mix proportion of substrates was ascertained. For the total processing capacity of 700,000 t/a from the Indian tanning industry, the potential for bioenergy generation and greenhouse gas emission reductions was estimated at 52.15 × 106 kWh/y and 0.3 × 106 t CO2-eq/y, respectively. There is a vast scope for the Indian tanning industry to benefit from tapping of bioenergy and carbon credits under the clean development mechanism.

Blockchain-Based Waste Energy Traceability for Sustainable and Digitally Transformed Supply Chains: A Case Study in the Leather Industry

Objectives: To examine how human capital influences the environmental engagement of SMEs in Pakistan’s leather industry. Another objective is to explore the different motivations of SME owners and managers for adopting the pro-environmental behaviour in this industry sector. Prior Work: The research is informed by literature on SMEs and environmental responsibility. Previous research has identified a number of internal and external drivers of, and barriers to, the environmental engagement of SMEs, but much of this research has focused on developed economies. Moreover, research looking specifically at the resources, capabilities and internal processes remains limited. Developing economy-focused research can complement and counterpoint the developed economy orientation of existing work. A focus on environmental practices of SMEs in less familiar cultural settings can also provide new insights. Approach: The research study adopts a qualitative approach and uses multiple case study research design. Guided by the evidence collected in a preliminary literature review, purposive and snowball sampling techniques were used to select a suitable sample of SMEs. Semi-structured interviews were conducted, transcript evidence was combined with observational and documentary sources, and the cases were refined using thematic analysis technique. Results: Contrary to prior research, which regards regulatory compliance as the leading motivation for environmental engagement among SMEs in developed economies such as the EU, this study suggests that, in Pakistan, a primary factor is the presence of, and commercial pressure from, environmentally-conscious customers. The variation in findings can be attributed in part to context-specific factors. Drawing on the human capital literature, this study found that owner managers with higher educational attainment, tended to be more aware of both the challenges and the opportunities in adopting new environmental practices. However, some of the educated owner-managers had a lower level of environmental awareness, which hindered the environmental engagement of their businesses. It also appears that the owner-managers in this study would be more likely to invest in such initiatives through economic incentives, rather than as a consequence of adopting a sustainability agenda or acknowledging a wider responsibility for the natural environment. Value: The findings of the study are important in policy terms, given their focus on the enabling features of human capital in promoting environmental practices in developing economies. There is considerable scope for national governments and international donor agencies to launch environmental awareness programmes for SMEs, which should not simply educate entrepreneurs and employees, but also inspire them to pursue environmental opportunities.

The basic objective of long-term optimization of large-scale hydropower system operations (LOLHSO) is to increase water resource use efficiency and construct a clean and low-carbon-intensity energy system. However, limited by rather stochastic inflows, large-scale hydropower systems, and complex objectives and constraints, LOLHSO is characterized by uncertainty, high dimensionality, nonlinearity, and nonconvexity, which pose great challenges in modeling. This paper presents an improved hybrid decomposition-coordination and discrete differential dynamic programming model (IDC-DDDP) for solving the LOLHSO problem. In IDC-DDDP, a decomposition strategy considering the adjustment potential of hydropower plants is designed to reduce the system size. Meanwhile, owing to the sensitivity of DDDP to initial trajectories, a data mining–based strategy is developed as a means of generating superior initial trajectories. A corridor generation strategy is presented to determine the discrete steps and enhance global search abilities. Case studies in a hydropower system in southwestwern China demonstrate the practicability and robustness of the proposed model.

Potential to Produce Biogas from Tannery Waste

This paper investigates the integrated scheduling of distributed energy resources and electric vehicles in isolated microgrid. The multi-types renewable energy sources management model considering photovoltaic, wind turbine, diesel generator, battery and fuel cell is proposed. The objective of the proposed optimal scheduling problem is to minimize the total cost of operational cost and environmental management cost. Besides differential search algorithm approach to the optimal scheduling problem is applied. A case study with an isolated microgrid including a fleet of electric vehicles is used to illustrate the performance of the differential search algorithm. The results show that the proposed coordinated scheduling strategy of microgrid with electric vehicles satisfies economic goals and differential search algorithm has competitiveness to traditional intelligent algorithm in solution for scheduling of microgrid.

This paper sets out to analyze a case study of ABC, one of the leading manufacturers of automobiles in India to assess its current status of reverse logistics operations. A situation-actor-process (SAP)-learning-action-performance (LAP) model has been applied to analyze the case study. Literature review indicates that issues like regulations, top management commitment, competition in market, and state of art information technologies are needed for successful reverse logistics programs. Very few frameworks of reverse logistics have been reported in literature that give a holistic perspective of reverse logistics operations in automobile industry. Results of case study indicate that reverse logistics operations at ABC are mainly confined to warranty components to gain goodwill of customers. Also, financial constraints and lack of appropriate performance metrics were the chief barriers affecting reverse logistics operations at ABC. Results of study reveals that though Indian automobile companies have begun to embrace reverses logistics practices, ample opportunities for improvements are still possible. The present SAP-LAP framework is useful in understanding issues related to strategic, tactical and operational level issues of reverse logistics. Managers can gain useful insights by understanding the interplay among situation, actor, and process. The synthesis of SAP leads to LAP, which suggests improvement actions based on the gaps of present situation, actors, and processes which could be useful for logistics managers.