Abstract
Manufacturing, a vital global economic sector, drives growth and innovation. However, its environmental impact is significant. World Economic Forum statistics from March 2022 reveal that production sectors consume 54% of global energy and contribute to 20% of carbon emissions. These factors lead to global warming and climate shifts, emphasizing the need to integrate green practices into manufacturing. Industry 4.0, driving digital transformation in manufacturing, offers potential to mitigate environmental effects. Technologies like IoT, big data analytics, AI, and additive manufacturing play key roles. This paper conducts a systematic literature review, analyzing research to explore sustainability through Industry 4.0 in manufacturing. Findings present a framework integrating lean production, life cycle assessment, circular economy, zero-defect manufacturing, and supply chain management with digital technologies. The goal is to achieve environmental sustainability in energy efficiency, waste management, resource efficiency, and emission control domains.
Research Objectives
This paper explores how digital transformation influences the adoption of environmentally friendly practices in manufacturing. The primary and sub-research questions (discussed in section 3.1) focus on the relationship between manufacturing approaches, green practices, and Industry 4.0 concepts for reducing environmental impact and promoting sustainability. The systematic literature review, conducted using PRISMA and SPAR-4-SLR protocols, provide a framework that describes the integration of leading manufacturing methods such as lean production, life-cycle assessment, circular economy, zero-defect manufacturing, and supply chain management with digital technologies to achieve environmental sustainability in the four domains of energy efficiency, waste management, resource efficiency, and emission control.
Conceptual Background
The need for a sustainable future and its intersection with growing manufacturing demands is complicated and requires comprehensive research on various domains. In this section, relevant concepts and strategies will be covered to build on the knowledge of theoretical foundations before conducting the systematic literature review.
Sustainable Manufacturing
The concept of sustainability has its origins in several disciplines and historical movements. While there is no single source, various significant events and ideas have contributed to its growth over time. One of those events has been the famous Brundtland Commission in Geneva in 1987, which is remembered even today for its signature idea of sustainable development put forward in the report ‘Our Common Future’ (Borowy, 2013). This report presented by the World Commission on Environment and Development explained sustainable development as the one that fulfills the requirement of the existing generation without compromising the capacity of future generations to satisfy their own requirements (Brundtland, 1987). Widely acknowledged and accepted as a formal understanding of sustainability, this definition elaborates on intergenerational equality as a core idea of sustainable development, emphasizing the need of maintaining resources for future generations. This concept distinguishes sustainable development strategy from traditional environmental policies, which largely focus on internalizing the external costs of environmental damage (Emas, 2015).
Green Manufacturing
Green manufacturing involves eco-friendly and sustainable production practices, aiming to minimize environmental impact, ensure resource efficiency, and promote clean technologies throughout the product life cycle (Deif, 2011). It emphasizes reducing pollution, optimizing resource utilization, and minimizing energy consumption for a sustainable and environmentally friendly industrial sector (Lin et al., 2020). “Green” can also be an action verb, reflecting intentional efforts to mitigate ecological implications, such as minimizing hazardous waste and optimizing energy sources (Dornfeld, 2012). Ongoing research explores innovative approaches and technologies to advance the greening of manufacturing processes, contributing to a more sustainable industrial landscape.
Key Terms in this Chapter
Energy Consumption and Emissions: Refers to the amount of energy required to manufacture products and the emissions resulting from production processes. Reducing these are significant goals of sustainable manufacturing that aim to lessen the environmental impact and combat climate change.
Data-Driven Control: Entails using data analytics and insights to guide decision-making processes in manufacturing. By collecting and analyzing real-time data, manufacturing systems can optimize production, reduce waste, and enhance quality control.
Life Cycle Assessment (LCA): This environmental management tool evaluates the environmental impacts of a product or service throughout its life cycle, from raw material extraction to disposal, including all stages of production, use, and end-of-life management. LCA is used to identify opportunities to improve the environmental performance of products at various points in their life cycle.
Lean Production: A manufacturing methodology that seeks to cut out waste and inefficiency, streamline production processes, and enhance product quality. Lean manufacturing principles are often combined with Industry 4.0 technologies to further optimize supply chains and operational efficiency.
Cyber-Physical Systems (CPS): The integration of computation, networking, and physical processes. Embedded computers and networks monitor and control the physical processes, with feedback loops where physical processes affect computations and vice versa. CPS is central to Industry 4.0 as it leads to improvements in automation and operational efficiency.
Zero Defect Manufacturing (ZDM): An approach that seeks to eliminate defects in the manufacturing process, resulting in a reduction of waste and environmental impact, while optimizing manufacturing efficiency. ZDM integrates Industry 4.0 technologies like artificial intelligence and big data analytics to support quality control and operational improvements.
Industry 4.0: The melding of traditional manufacturing and industrial practices with the latest smart technology. This revolution includes advanced automation, data exchange, AI, cyber-physical systems, and IoT, leading to smarter, more efficient production lines that can adapt in real-time to changing demand or conditions.
Sustainable Manufacturing: The manufacturing of goods with a minimal negative environmental impact through energy and resource-efficient processes. It includes the adoption of practices and technologies that do not deplete or harm natural resources and are compliant with environmental legislation.
Additive Manufacturing (AM): Also known as 3D printing, this process involves creating objects by adding material layer by layer, which allows for complex designs and often results in less material waste compared to subtractive manufacturing processes. AM is considered a key aspect of Industry 4.0 for its role in enabling rapid prototyping and customization.
Environmental Impact: The effect of manufacturing activities on the natural environment, including resource depletion, pollution, and waste generation. Minimizing environmental impact is a critical objective of sustainable manufacturing initiatives.
Systematic Literature Review: A research method that involves a comprehensive summary and analysis of existing literature on a subject area. It aims to identify, appraise, and synthesize all the empirical evidence that fits pre-specified eligibility criteria to answer a particular research question.
Resource Optimization: Involves the strategic utilization and management of resources in the most efficient manner possible. It can include better planning, adopting new practices or technologies, and reducing waste of raw materials, water, and energy.
Digital Transformation: Refers to the comprehensive change that organizations undergo by leveraging digital technologies to reinvent operational processes, business models, and customer experiences. It usually entails integrating technologies like big data, the Internet of Things (IoT), and artificial intelligence (AI) to streamline operations, boost productivity, and facilitate innovation.
Circular Economy: A systemic approach to economic development designed to benefit businesses, society, and the environment by keeping products and materials in use, designing out waste and pollution, and regenerating natural systems. It represents a shift from the traditional take-make-waste linear model to one that is restorative by design.