Global Manufacturing Research Articles

BUSINESS STRATEGIES OF CAR BRANDS ON THEIR PATH TO SUSTAINABILITY

The article is dedicated to examining the structure of business strategies of several large car brands within the context of achieving sustainable development goals. To conduct this research, the authors have used information from annual, integrated, or sustainability reports of seven global car manufacturers for 2023. The authors disclose a reason for indicating automobile manufacturers as pivotal market actors in ensuring sustainability under the stable economic growth. The article outlines key elements of business strategies of these global car brands for the next decade. The authors determine the conformity between the considered strategic initiatives and the sustainable development goals. The authors ascertain what considered strategic initiatives aren’t directly connected to achieving sustainability. The article summarizes general tendencies in establishing development goals by the car manufacturers.

Impact of large-scale renewable energy integration on the grid voltage stability

Nowadays, the production of renewable energy is increasing rapidly due to its enormous potential and environmental advantages. Still, the addition of renewable energy to the grid has resulted in some volatility in the electrical system. In this work, the national grid of Ethiopia is used as an example to examine the impact of significant wind power integration on grid stability. In particular, issues with voltage stability in both steady-state and emergency scenarios are taken into account for the network. The dynamic modeling of the wind farm is taken into consideration for contingency-based analysis, and the whole nation's power network, including the largest wind farm in the nation, Adama-II, is modeled for base-case analysis using MATLAB's built-in PSAT software. The result indicates that the bus voltages are within an acceptable standard voltage range for the base-case system. Nevertheless, the wind farm will be disconnected from the network in compliance with the global manufacturer's guideline in the case of a three-phase fault at the network point of common coupling (PCC), where the voltage at PCC is equivalent to 0.045 per unit voltage. The results also demonstrate that the voltage profile throughout the whole nation power network is lower when there is a problem at PCC. As a result, as Ethiopia is building several huge wind farms, it is advised that fault detection and control methods be thoroughly designed before connecting the major wind farms to the grid.

Transforming Inventory Management for Global Manufacturing Efficiency

This qualitative study explores the application of raw material inventory accounting information systems and internal control measures at PT. Perdana Sukses Makmur, a manufacturing company in Indonesia. Through interviews, observation, and documentation analysis, the research identifies that while the company's inventory system is well-implemented, certain internal control measures, such as the combination of functions and responsibilities, require improvement. These findings contribute to understanding inventory management practices in manufacturing firms, suggesting areas for enhancing internal control to improve production efficiency and organizational performance. Highlight: Efficient Inventory System: PT. Perdana Sukses Makmur demonstrates effective inventory management practices. Internal Control Challenges: Addressing function combination enhances organizational oversight. Production Efficiency Implications: Refining internal controls enhances manufacturing performance. Keywoard: Inventory Management, Internal Control, Manufacturing Company, Qualitative Study, Indonesia

Analysis and Reflection on the Strategy Benchmarking of Power Battery Management in China and Europe

In 2023, the European Union (EU) enacted the Regulation on Batteries and Waste Batteries (hereinafter referred to as the New Law on Batteries), which strengthens the regulatory framework for the entire lifecycle of power batteries. This development presents both challenges and opportunities for global power battery manufacturers and operators. As a significant player in the global power battery industry chain and the world’s largest producer of electric vehicles and power batteries, China must systematically assess the impact of global battery management strategies, including the EU’s New Law on Batteries, from a lifecycle perspective. This understanding is crucial for maintaining China’s competitive edge in the global power battery market and achieving mutually beneficial outcomes in international trade negotiations. This paper constructs a strategy analysis framework based on the lifecycle approach. By summarizing the power battery management strategies of both the EU and China, it provides a comprehensive overview of strategies across different countries, highlights the key regulatory focus areas, and offers relevant strategy recommendations. The main conclusions and insights are as follows: (1) The New Law on Batteries achieves lifecycle regulation from “cradle” to “grave” and back to “cradle”. (2) China emphasizes the management of waste power batteries, with an increasingly robust strategy system at the recycling stage, yet lacks comprehensive measures for other lifecycle stages. (3) The EU has established a comprehensive lifecycle strategy management system centered on the New Law on Batteries, characterized by strong coordination and a synergistic combination of strategies across different sectors. Finally, this paper identifies three major compliance challenges posed by the New Law on Batteries, necessitating enhanced strategy development and implementation in the areas of carbon footprint management, circular economy, and digital battery passports.

Regulatory Compliance of Cosmetic Products in Kenya: A Narrative Review on Quality and Safety

This study reviews the regulatory compliance of cosmetic products in Kenya, with a focus on consumer risks and potential public health impact. A narrative review study design was employed and a literature search was conducted using government reports, publications, academic databases, and other relevant sources. Keywords such as cosmetic industry challenges and cosmetic regulation in Kenya were employed to search the literature for papers. Data focusing on regulatory frameworks, enforcement mechanisms, adverse reactions, and industry challenges was then extracted and discussed in the form of a narration. The growth of the cosmetic industry, fueled by urbanization, a rising middle class, and increased grooming awareness, has attracted both local and international investors, presenting challenges in maintaining product quality and safety standards. Seven cases of adverse reactions related to cosmetics were reported by Pharmacy and Poisons Board between 2018-2023. The current study identifies noteworthy challenges by examining Kenya’s regulatory framework, led by the Pharmacy and Poisons Board and the Kenya Bureau of Standards. Enforcement disparities within international standards, variance in regulations on prohibited ingredients, inconsistent labeling requirements, industry dynamics, and counterfeiting, compounded with the complex nature of safety assessments raise concerns for cosmetic regulators, distributors, and manufacturers. The study highlights existing gaps in regulatory oversight emphasizing the necessity of robust enforcement mechanisms. Compliance assessments by KEBS and PPB encompass the evaluation of ingredients, formulations, microbial contamination, packaging, and labeling. Factors contributing to regulatory noncompliance include poor product quality aggravated by supply chain complexities in the vast and diverse sector. The cosmetic cottage industry inadvertently presents a quality risk to consumers due to limited process and testing capacity. Reported adverse reactions, particularly to mercury-containing skin-lightening products, raise concerns about public health implications. This study advocates for continuous product monitoring and heightened vigilance. The review proposes improvement strategies, emphasizing a dynamic regulatory approach, periodic ingredient reviews, a centralized product approval system, and alignment with global manufacturing standards. Targeted consumer education initiatives focusing on product quality attributes, adverse reaction reporting, label reading, and counterfeit awareness are recommended.

A comprehensive review on fresh and rheological properties of 3D printable cementitious composites

The undeniable potential of 3D printing technology to revolutionize global manufacturing processes has led to the emergence of advanced, digitalized, and fully automated construction techniques. Despite the growing interest in this technology, a significant challenge still exists in the development of cement-based printing material due to the complex interaction of various fresh and rheological property parameters. This review comprehensively explores fundamental fresh properties (flowability, buildability, extrudability, pumpability and open time) and rheological properties (static yield stress, dynamic yield stress, plastic viscosity) essential for the formulation of 3D printable cementitious composites, with and without fibres. The results obtained from different rheometers for successful 3D printed mixes are also summarized, highlighting variation in recorded values. Moreover, the review thoroughly investigates factors affecting both fresh and rheological properties, such as the type of supplementary cementitious materials, fibre type and dosage, superplasticizer, and viscosity-modifying admixture. It also identifies the clear impact of these parameters and further recommends the optimal range of some properties, such as a flowability value between 160 and 200 mm, to achieve desirable 3D printability of cementitious composites. Overall, this review offers valuable insights for developing new mix compositions suitable for 3D printing and serves as a useful tool in establishing guidelines for 3D printable cementitious composite materials, which are currently lacking but crucial for research, development, and application in this field.

Evaluating industry 4.0's sustainable performance and its impact on the manufacturing strategies

Industry 4.0 (I4.0) standards have gradually being implemented as an advanced approach to manufacturing in the developed and developing nations. The ability of an enterprise to succeed in a highly-competitive global manufacturing market is dependent on various manufacturing strategy outcomes (MSOs), such as cost, quality, delivery, flexibility, and innovation. These MSOs play a vital role in shaping the organization's overall competitive edge. Existing scientific literature indicates that there is currently uncertainty regarding how the many cutting-edge technologies addressed within I4.0 are going to impact MSOs. The key objective of the present research is to examine the impact of I4.0's sustainability on MSOs’ ability to survive and thrive in a highly competitive environment, as considered by academic and industrial experts. In order to understand more about how MSOs and I4.0's sustainable performance are related, experts were interviewed. The findings demonstrated strong links that encourage the adoption of I4.0 sustainable performance approaches, which can offer organizations with a distinct competitive advantage over their competitors. The findings suggested that MSOs have a high potential for synergistic collaboration with several aspects of I4.0's sustainability.

How power structure and markup schemes impact supply chain channel efficiency under price-dependent stochastic demand

Although considerable attention has been separately given to factors such as power structures, price-dependent demand, and markup pricing schemes, there has been limited exploration of the combined effects of these factors on supply chain efficiency and the leader’s advantage. We propose a game theoretic model in which a manufacturer sells a single product to a newsvendor retailer who sets both optimal order quantity and selling price under uncertain price-dependent demand. Furthermore, we examine a supply network wherein a single retailer fulfills orders using a global manufacturer for regular orders and a local manufacturer to clear any shortages. Through numerical analysis, we show that the retailer always prefers to charge a percentage markup. In a two-player game, channel efficiency is higher when the retailer is the leader under linear demand; however, under iso-elastic demand, the manufacturer being a leader brings a higher channel efficiency. When a local manufacturer is involved as a second manufacturer, channel efficiency is higher when the retailer remains a follower, as this induces more fierce wholesale price competition between the two manufacturers. Additionally, when demand uncertainty is high in the two-player game with linear demand, the retailer as a follower can achieve higher profits, whilst high uncertainty under iso-elastic demand decreases both players’ profits. Moreover, it becomes advantageous for the retailer to have a local manufacturer as demand uncertainty increases, even when the local manufacturer announces the wholesale price first.

Blockchain‐enabled decentralized service selection for QoS‐aware cloud manufacturing

AbstractIn recent years, cloud manufacturing has brought both opportunities and challenges to the manufacturing industry. Cloud manufacturing enables global manufacturing resources to be unified and shared, thus breaking down geographical constraints to enhance the level and efficiency of manufacturing. However, with the explosive growth of manufacturing resources and user demands, traditional cloud manufacturing platforms will face problems of insufficient computility, lack of real‐time data and difficulties in securing user privacy during the service selection process. In this article, a blockchain‐based decentralized cloud manufacturing service selection method is proposed, where the computility resource is deployed in multiple distributed nodes rather than the traditional centralized cloud manufacturing platform to solve the problem of insufficient computility. The credibility of the users is evaluated based on their performance on the contract and the PBFT consensus algorithm is improved based on the credibility of the users. In addition, a tri‐chain blockchain data storage model is designed to ensure the security, real‐time and transparency of data in the cloud manufacturing service selection process. The experimental results show that the method both speeds up service selection process and improves the quality of service selection results, and achieves a significant increase in manufacturing efficiency.

Product Customization and Returns: The Moderating Role of National Culture

Product customization enables consumers to tailor products to their individual preferences. One benefit of customization is its lower volume of returns. By customizing, consumers learn about their product preferences and develop a sense of attachment to the products they help “create.” As a result, they are less likely to return the purchased items. The effect of product customization on returns may depend on cultural traits of consumers, such as the extent to which they would avoid uncertainty or the degree to which they would feel “subordinate” to authority. Hence, this article studies how national culture moderates the negative relationship between customization and returns. Our investigation analyzes a unique dataset from a leading global luxury brand manufacturer that offers both standard and customized versions of a product across more than 20 countries. We find that the disparity in return rates between standard (higher rate) and customized products (lower rate) depends on the cultural dimensions originally introduced by Hofstede. This gap widens with masculinity and uncertainty avoidance but narrows with power distance and individualism. Therefore, multinational firms should weigh these aspects of national cultures when designing both customization and return policies.

Digitalisation On Automotive Supply Chain for Climate Competitiveness: A Systematic Bibliometric Analysis

The automotive industry, a cornerstone of global manufacturing, is undergoing a profound transformation driven by digitalization. This research paper explores the impact of digitalization on the automotive supply chain and its role in enhancing climate competitiveness. As the industry strives to meet stringent environmental standards and consumer demands for sustainability, leveraging digital technologies becomes imperative. We use R Studio software to perform bibliometric analysis in this study. Our initial repository for data came from the Scopus database. Following a keyword search and before applying the limited criteria, we were able to find 3202 papers. We then started integrating the limited criteria, which included the following: stream: Business Management & Accounting, source type: Journal, no author, duplicate titles, and language: English. After applying these criteria, we were able to find 935 papers. We selected citations, bibliographical data, abstracts and keywords, funding information, and other data before exporting our database from Scopus.

Emission calibrated traffic model for environmental-sensitive decision making in Sri Lanka: Review

Air pollution from road transportation is a growing concern in urban areas, particularly in Sri Lanka, where vehicle emissions account for a significant portion of air pollutants. The increase in the number of vehicles on the road and the resulting traffic congestion exacerbate this problem. Therefore, accurate prediction of emissions and air quality related to road traffic is essential for informed decision-making in traffic planning and management. While Sri Lanka has made progress in developing driving cycles and traffic flow simulations tailored to its unique context, there remains a gap in calibrating these models with local emission values, which are influenced by specific driver behaviours and operational modes. An emission-calibrated traffic model specific to the Sri Lankan context can integrate both traffic-related and environmental factors, providing a comprehensive tool for analyzing the impact of traffic management strategies on emissions and air quality. By addressing the discrepancies between global manufacturer data and local conditions, this model can enable more environmentally friendly decisions in urban transportation planning, contributing to the reduction of air pollution. The study identifies, through a comprehensive review, the need for an emission-calibrated traffic model to address the unique challenges posed by Sri Lanka's evolving traffic landscape. While traffic modelling has made strides in Sri Lanka, this study identifies a significant research gap in modelling the emissions generated by these traffic models, especially considering the unique characteristics of the region's roads and vehicles. Further, the paper concludes that an emission-calibrated traffic model specifically tailored to the Sri Lankan context is essential to guide environmentally friendly traffic planning decisions and bridge the gap between traffic data and its environmental consequences.

ROLE OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING IN OPTIMIZING INVENTORY MANAGEMENT ACROSS GLOBAL INDUSTRIAL MANUFACTURING & SUPPLY CHAIN: A MULTI-COUNTRY REVIEW

This study examines the impact of Artificial Intelligence (AI) and Machine Learning (ML) on inventory management within global industrial manufacturing and supply chains, particularly in the context of Industry 4.0. Through a comparative analysis across several countries, the research analyzes quantitative and qualitative data to assess the adoption and integration of these technologies and their implications for supply chain optimization. The research methodology includes a comprehensive literature review using multiple databases and expert interviews conducted within a specific timeframe. The study identifies a significant favorable influence of AI and ML on enhancing efficiency, reducing costs, and improving real-time data analytics and predictive maintenance. It highlights the evolution from theoretical potential to practical applications, with an increased focus on regulatory compliance and data integrity, reflecting the industry's maturation in digital integration. Furthermore, the study explores the strategic role of AI and ML in process design and the holistic adoption of Industry 4.0 principles across the supply chain. The findings contribute to the academic literature by detailing the benefits and challenges of AI and ML implementation, offering insights for future research and practical applications in the supply chain sector. The conclusion emphasizes the transformative potential of AI and ML, advocating for their strategic implementation to foster resilience and adaptability in supply chain networks.

Aligning production requirements with product and production maturities: enhancing production preparation during product development

AbstractProduct development is multidisciplinary with high uncertainties necessitating coordinated decision-making between design and production. This paper presents a method to work with production requirements to support production preparation during product development aligned with different product and production maturities. The work was conducted in collaboration with two global manufacturing firms. The method supports identification, definition, and structuring of production requirements and the collaboration between design and production engineers for requirement prioritization and follow-up.

An innovative “Up-and-Down” adsorption processes for pyrene removal from acid wastewater as new approach in water remediation

Polycyclic Aromatic Hydrocarbons (PAH) pose a risk to human health because they are highly toxic, carcinogenic, and mutagenic. In the context of water remediation, hybrid biopolymers are green materials that can reduce the pollutants in environmental matrices. This study aims to propose a new “up-and-down” wastewater treatment system based on the adsorption of contaminants from the bulk and their transport to the surface to promote future remediation processes. Pyrene was selected as a model pollutant for PAH, and hybrid alginate beads, such as thermally modified hematite montmorillonite alginate calcium carbonate beads (@H@MACaBs), were prepared to investigate their use in water remediation. The synthesized beads were characterized using FT-IR SEM and ion-TOF mass spectrometry techniques, and adsorption studies were performed to quantify the remediation process efficiency and investigate the adsorption processes. Approximately 50 % of pyrene was removed from the aqueous solution without stirring after 90 min of contact. A double increase in pyrene removal was observed when the classical hybrid alginate beads were compared with the new modified hybrid alginate beads. This study contributes to efforts to deploy innovative remediation strategies to reduce the environmental impact of the textile industry, which is a significant contributor to global manufacturing and pollution.

A fine balance: A review of incinerators for menstrual waste and recommendations for policy and practice

ABSTRACT Menstrual health and hygiene is a public health and human rights issue. Amid growing access to menstrual health products and education, there is limited focus on end-of-life management and environmental impact of single-use products. Burning is a common practice to dispose of pads globally, with pad incinerators becoming widely available in India and parts of sub-Saharan Africa. However, known literature does not provide insights into the current product landscape for practitioners, researchers, or funders. Thus, this review aimed to identify and characterize incinerators designed specifically for menstrual pads and to propose recommendations for effective onsite incineration. Incinerators were identified using Internet searches, web forum posts, and key informant interviews. A custom coding form documented and summarized product characteristics. An estimate of the total cost of ownership (TCO) was computed. The ‘Availability, Accessibility, Acceptability, Quality’ framework was adapted to identify technology strengths and failures. This review identified 69 incinerators from 30 global manufacturers. Estimates of a 10-year TCO ranged from USD 153 to 149,900, with electricity being the largest driver of cost. Incinerators were found to largely lack safety features, such as emissions controls. This review provides key recommendations for a variety of stakeholders, including manufacturers, policymakers, regulators, researchers, and technical experts.

Analogical environmental cost assessment of silicon flows used in solar panels by the US and China

Achieving carbon neutrality requires deployment of large-scale renewable energy technologies like solar photovoltaic (PV) panels. Nevertheless, methods to ascertain the overall environmental impacts PVs and further improve their sustainability are under-investigated. In an effort to provide more understanding of this crucial topic, this research focuses on silicon flows—a key element for manufacturing crystalline silicon PVs. Using system dynamics modeling, we conduct a comprehensive environmental cost assessment of the silicon flows used in PVs based on a comparative analysis between the United States and China as the leading global PV manufacturers. Despite the advancement in wafer quality, material usage reductions and overall price decreases achieved in recent decades, our results project a substantial increase in energy and water consumption in China related to Metallurgical Grade Si (MG-Si), Solar Grade Si (SoG-Si) and cell manufacturing by 2030. An approximate 6.5 times increase of energy and water consumption is observed for c-Si cell manufacturing in China between 2010 and 2020. In 2030, increases of 70% in energy consumption and 69% in water use are estimated for Chinese MG-Si and SoG-Si production. The most significant environmental impact is observed in silicon cell and module manufacturing in both countries, particularly concerning GHG, SOx and NOx emissions. This study provides valuable insights into the environmental impacts of these two major solar panel manufacturing countries by examining the silicon life cycle, from production to end-of-life.

Additive Manufacturing: A Comprehensive Review.

Additive manufacturing has revolutionized manufacturing across a spectrum of industries by enabling the production of complex geometries with unparalleled customization and reduced waste. Beginning as a rapid prototyping tool, additive manufacturing has matured into a comprehensive manufacturing solution, embracing a wide range of materials, such as polymers, metals, ceramics, and composites. This paper delves into the workflow of additive manufacturing, encompassing design, modeling, slicing, printing, and post-processing. Various additive manufacturing technologies are explored, including material extrusion, VAT polymerization, material jetting, binder jetting, selective laser sintering, selective laser melting, direct metal laser sintering, electron beam melting, multi-jet fusion, direct energy deposition, carbon fiber reinforced, laminated object manufacturing, and more, discussing their principles, advantages, disadvantages, material compatibilities, applications, and developing trends. Additionally, the future of additive manufacturing is projected, highlighting potential advancements in 3D bioprinting, 3D food printing, large-scale 3D printing, 4D printing, and AI-based additive manufacturing. This comprehensive survey aims to underscore the transformative impact of additive manufacturing on global manufacturing, emphasizing ongoing challenges and the promising horizon of innovations that could further elevate its role in the manufacturing revolution.

Building a knowledge graph to enrich ChatGPT responses in manufacturing service discovery

Sourcing and identification of new manufacturing partners is crucial for manufacturing system integrators to enhance agility and reduce risk through supply chain diversification in the global economy. The advent of advanced large language models has captured significant interest, due to their ability to generate comprehensive and articulate responses across a wide range of knowledge domains. However, the system often falls short in accuracy and completeness when responding to domain-specific inquiries, particularly in areas like manufacturing service discovery. This research explores the potential of leveraging Knowledge Graphs in conjunction with ChatGPT to streamline the process for prospective clients in identifying small manufacturing enterprises. In this study, we propose a method that integrates bottom-up ontology with advanced machine learning models to develop a Manufacturing Service Knowledge Graph from an array of structured and unstructured data sources, including the digital footprints of small-scale manufacturers throughout North America. The Knowledge Graph and the learned graph embedding vectors are leveraged to tackle intricate queries within the digital supply chain network, responding with enhanced reliability and greater interpretability. The approach highlighted is scalable to millions of entities that can be distributed to form a global Manufacturing Service Knowledge Network Graph that can potentially interconnect multiple types of Knowledge Graphs that span industry sectors, geopolitical boundaries, and business domains. The dataset developed for this study, now publicly accessible, encompasses more than 13,000 manufacturers’ weblinks, manufacturing services, certifications, and location entity types.

Optimal Emergency Order Policy for Supply Disruptions in the Semiconductor Industry

Semiconductor materials are strategic materials in global manufacturing. Affected by supply chain risks, semiconductor supply shortages have brought unprecedented pressure on global supply chain security, such as car manufacturers and electrical and electronic production stopping production among others, resulting in economic losses. When supply disruption occurs, retailers typically place emergency orders to reduce unexpected costs caused by the event. This study examines the emergency ordering problem faced by retailers under supply disruptions in the semiconductor industry, using the supply of semiconductor chips from Renesas Electronics to Toyota as an example. For this, we establish an emergency ordering optimization model based on retailers' profit maximization and solve it by modelling analysis. The model's validity and the impact of parameters on emergency ordering policy are verified by numerical experiments. The experimental findings demonstrate that: first, the retailer should consider the impact of consumer demand, alongside market price volatility, and make reasonable arrangements for the replenishment time and quantity. Second, at a higher partial backordering rate, the retailer makes larger adjustments for partial backordering by increasing the backordering quantity and making more profits. Third, in the case of shortages, the greater the shortage penalty cost is, the lower the profits the retailer gains, making it necessary to develop a timely replenishment strategy to prevent losses caused by shortages in semiconductor supply chain systems. Thus, in the event of a disruption, retailers should ensure that their order quantities not only meet market demand but also consider inventory holding costs while judiciously determining the number of emergency orders. This study addresses real-world scenarios in the semiconductor industry's supply disruptions and aids managers in formulating optimal emergency ordering strategies to maximize profits and ensure business continuity.