Manufacturing Supply Networks Research Articles

Delivering HIV and TB services amidst the COVID-19 pandemic in Indonesia: a qualitative study of challenges and mitigation strategies

Background Indonesia has the second-highest burden of tuberculosis (TB) globally and is experiencing one of the fastest-growing HIV epidemics worldwide. The COVID-19 pandemic disrupted access to essential health services, including those for TB and HIV, due to health system overload, social distancing measures, and negative economic repercussions on the health sector and the population. An in-depth understanding of these challenges and the health system responses to mitigate the negative impact of the pandemic on TB and HIV services is crucial to building health system resilience and preparing for future emergencies. Methods This qualitative study, conducted in two cities in Indonesia, explored the impact of the COVID-19 pandemic on TB and HIV services including mitigation strategies to sustain the provision of testing and treatment in the midst of the pandemic. Between February and June 2022, semi-structured interviews were conducted with 16 healthcare workers and 16 clients at nine health centers (puskesmas), three hospitals, and one Community Center for Lung Health in Bandung and Yogyakarta. Themes were identified from transcripts using open and selective coding and then refined. Results Extraordinary measures were implemented in health facilities to sustain TB and HIV service delivery, and prevent the spread of COVID-19, including testing of clients for COVID-19 before receiving medical care, physical distancing when visiting healthcare facilities, revised schedules for medicine dispensing, involvement of community health workers and peers in community outreach activities such as the home delivery of medicines, and the use of telemedicine. Challenges encountered during the implementation of these strategies included medicine stock-outs, health worker overload, lack of sufficient client-provider interaction and technical difficulties when implementing telemedicine, and the risk or fear of exposure to COVID-19 among the community health workers and peers. Conclusions Significant efforts were made to mitigate disruptions to TB and HIV services during the COVID-19 pandemic. However, some challenges were encountered. Key policy recommendations to strengthen pandemic preparedness include investing in local manufacturing and robust drug supply networks to prevent medicine shortages, and supporting community health workers to alleviate workload issues, reduce the risk of disease exposure, and explore the potential for a financial incentive system. Equally vital is the need to invest in staff training and education, as well as implementing user-friendly telemedicine technologies.

A Decision Support Framework for Robust Multilevel Co-Design Exploration of Manufacturing Supply Networks

Abstract The design of a manufacturing supply network (MSN) requires the consideration of decisions made by different groups at multiple levels and their interactions that include potential conflicts. Decisions are typically made based on information from computational simulations that are abstractions of reality and, therefore, embody uncertainty. This necessitates focusing on design space exploration to identify robust satisficing solution sets that are relatively insensitive to uncertainty. Current frameworks that support robust satisficing design space exploration are limited by their capability to support the efficient exploration of multilevel design spaces simultaneously. In this paper, we present the Framework for Robust Multilevel Co-Design Exploration (FRoMCoDE), a decision support framework that allows designers to (i) model decision problems across multiple levels and their interactions, (ii) consider uncertainties in the decision problems, and (iii) visualize and systematically carry out simultaneous exploration of multilevel design spaces, termed co-design exploration. In FRoMCoDE, we combine the coupled-compromise Decision Support Problem construct, where a combination of the Preemptive and Archimedean formulations is used, with robust design constructs and interpretable-Self-Organizing Maps (iSOM)-based visualization to facilitate robust co-design. We use a steel MSN problem with decisions made at two levels to test the framework. Using the problem, we demonstrate FRoMCoDE's efficacy in supporting designers in (i) modeling multilevel decision problems and their interactions, considering the uncertainties, and (ii) the efficient co-design exploration of multilevel design spaces. FRoMCoDE is generic and supports designers in the robust co-design exploration of multilevel systems.

How do suppliers respond to institutional complexity? Examining voluntary public environmental disclosure in a global manufacturing supply network

AbstractWhen making decisions about their commitments to environmental practices and performance, suppliers face heterogenous institutional logics and their diverse prescriptions for action. How do suppliers respond to such institutional complexity? We examine this question in the context of suppliers' voluntary public environmental disclosures (disclosure). Specifically, our study assembles a unique panel data set of global manufacturing suppliers and their annual contractual relationships with buyers. Building on the institutional logics perspective and the sustainable supply network literature, we hypothesize that suppliers selectively mimic the disclosure of their buyers by following market, corporate, and sustainability logics. Our study contributes to the institutional logics perspective and the sustainable supply network literature by indicating that in the context of disclosure, market and sustainability logics both actively shape suppliers' responses to institutional complexity. Furthermore, we find support for mimicry as a mechanism of buyer influence that can lead to disclosure heterogeneity across suppliers even when they follow the same logic, which opens new avenues for research. Our findings can be leveraged by buyers, policymakers, and other stakeholders interested in advancing transparency and sustainability in supply networks.

OPTIMIZING SUSTAINABLE MATERIAL SELECTION FOR AIR CONDITIONERS IN A SUPPLY CHAIN

In order to cut their carbon footprint and promote environmental sustainability, the majority of businesses have now turned towards sustainable practises in their manufacturing processes and supply networks. The use of sustainable materials has drawn a lot of attention recently as a crucial step in accomplishing these goals. Choosing the material that is most suited for a product can be difficult, despite the fact that there are many sustainable materials available. This study uses machine learning – a random forest algorithm and multi-criteria decision analysis (MCDA) to optimise the use of sustainable materials in supply-chain operations. The study uses machine learning algorithms to analyse data on different sustainable materials, their characteristics and their effects on the environment. The study also investigates how an optimised material selection affects the whole supply chain, including the production, packing and shipping operations. The research offers a complete strategy for reducing the environmental effect of industrial processes by combining approaches from material engineering, supply chain management and machine learning. The novelty of this work resides in its integration of material engineering and machine learning strategies to enhance the supply chain choice of sustainable materials. As a notable example, the study highlights the potential of mycelium as a sustainable material for air conditioner components. Mycelium’s unique properties, such as its biodegradability, lightweight nature and adaptability position it as a promising candidate, enhancing the environmental profile of air conditioners. By incorporating mycelium-based components, manufacturers can significantly reduce carbon emissions, resource consumption and waste generation throughout a product’s lifecycle. This investigation underscores both the viability of mycelium and the broader significance of innovative material choices in reshaping industries towards a more sustainable future. Through such advances, this research not only contributes to the air conditioning sector but also establishes a paradigm for sustainable material adoption with far-reaching positive implications.

A production bounce-back approach in the Cloud manufacturing network: case study of COVID-19 pandemic

ABSTRACT Industry 4.0 paradigm has enabled manufacturing systems with reformations for Cloud-based manufacturing business models. This reformation can create resilient structures as an inevitable opportunity for manufacturing supply networks. This is achieved by using service composition capabilities in Cloud manufacturing network which significantly enhances supply network performance when encountering disruptions. Focusing on redundancy as one of the most effective approaches to resiliency, a new model for manufacturing service composition is proposed. The model considers a minimum level of subentropy when responding to the demands at the process level while controlling the entropy overall at supply network level. This creates a balanced policy for entropy at the network level, and subentropies at the process level to both fulfill an optimal redundancy for disruption fulfillment and controling the complexity throughout the network. A case study is considered for manufacturing ventilator production COVID-19 pandemic. The capabilities of the proposed model for optimal application of unused firm capacities from other supply networks like military and university research groups have been discussed. The proposed model is also investigated for fulfillment of disruptions like COVID-19 equipment supply network with mentioned capabilities. These capabilities fulfill the transition of manufacturing business models to a service-oriented paradigm with resilient structures.

Research on the Model of Industrial Interconnection Intelligent Manufacturing Supply and Demand Network and Its Robustness

The industrial interconnection intelligent manufacturing supply and demand network is the carrier for the cooperation of related enterprises, and research on its evolution helps to optimize the cooperation between enterprises. This paper considers the factors that affect enterprise cooperation, applies consensus, disconnection, reconnection, and change of opinion into one model, and constructs two models of industrial interconnection intelligent manufacturing supply and demand networks. Because the industrial interconnection intelligent manufacturing supply and demand network is affected by certain factors, the network will be subject to fluctuations and the functions of the network will change. The smaller the function change, the higher the robustness of the model. The related topological structure statistics (such as clustering coefficient, average path length, and degree distribution) of the two models are analyzed, and the analysis results indicate that the network structure of the two models has changed. In addition, different attack algorithms are used to verify the robustness of the model. The experimental results show that under the four different attack algorithms, compared with the BA model, the two models proposed in this paper have stronger robustness. Research on the industrial interconnection of intelligent manufacturing supply and demand networks and its robustness optimization has certain guiding significance.

Proactive disruption impact assessment in manufacturing supply networks

ABSTRACT Companies are increasingly exposed to the risk profile of their supply network and managing this risk is gaining in importance in a tightly interconnected global and competitive business environment. More frequent and more severe supply disruptions have led to a growing interest in assessing their potential consequences. Therefore, in this paper four supply disruption indicators are derived to proactively assess the potential financial impact of supply disruptions. The stochastic nature of potential supply disruptions is modelled by adopting a Monte-Carlo and Value-at-Risk simulation approach: Quantitative, objective data and qualitative, subjective estimates by managers are combined to improve proactive risk-related decision-making at a company level. The developed methodology for deriving the supply disruption indicators is applied to a case study in a German manufacturing company in order to quantitatively assess differences in the disruption risk structures of various supply relations. The results of the study show that a Value-at-Risk approach based on Monte-Carlo simulation can be effectively adopted to assist supply managers in proactively identifying suitable risk mitigation strategies.

Supply Risk Exposure Measurement in Manufacturing Supply Networks: An Index Construction Approach

Although the topic of managing risk in supply networks is of increasing relevance and interest, only a limited number of empirical studies have been conducted to date. An instrument to measure the individual risk exposure of a manufacturing company arising from its supply network is still missing. This research gap is addressed by means of an index construction procedure. Data is collected based on an expert survey across manufacturing companies. The application of the proposed index could inspire future empirical research and thus may provide deeper insights into the management of supply risk and its interaction with other company-specific parameters.

Supply risk identification in manufacturing supply networks

PurposeManaging supply risk is gaining in importance in the tightly interconnected global economy. Identifying the relevant risks is the foundation of any risk management process. Therefore, the purpose of this paper first is to provide a short introduction to supply risk management, before focussing on the identification of such risks in more detail. A holistic framework of the identified supply risks, which distinguishes between risk dimensions and risk factors in manufacturing upstream supply networks, is proposed.Design/methodology/approachThis study applies a mixed methods research approach. Data are collected based on a structured literature review in combination with the analysis of company-specific documents and semi-structured expert interviews. Subsequently, a deductive content analysis is carried out to derive a holistic framework of supply risks, adapted to the manufacturing industry. For the external validation of the conceptual supply risk framework, additional experts from several manufacturing companies were consulted.FindingsBased on the definition and delimitation of supply risk, a categorization of supply risks is developed. The relevant literature, as well as expert interviews, lead to the distinction of six supply risk dimensions: quality, delivery, collaboration, economic, ambience and compliance. A total of 27 risk factors can be assigned to these dimensions. A holistic foundation for the management of supply risk is thus created.Originality/valueThis study provides a holistic framework of relevant supply risks in the context of the manufacturing industry. This overview of identified risks offers a novel perspective on risk in manufacturing supply networks that can be helpful in researching assessment and mitigation strategies. Despite the high relevance and popularity of this field of research, such an overview with a focus on manufacturing had not yet been made available in the literature. Building thereon, management approaches can now be developed to handle the risk arising from the upstream of the supply network.

Introduction to dynamics of manufacturing supply networks.

Manufacturing supply networks are complex dynamic networks that play a crucial role in the economy. Nevertheless, there are so far only few studies that apply modern tools of network science and dynamical system theory to the analysis of these networks. Here, we provide a brief introduction to these types of networks highlighting their basic organization, current challenges, and selected previous work. This paper serves as an introduction to a focus topic consisting of five papers by experts on supply network dynamics.

Rapid production ramp-up capability: a collaborative supply network perspective

This paper explores how technology intensive manufacturing firms operate to achieve rapid new product volume ramp-up capabilities within an international collaborative supply network. An exploratory multiple-case longitudinal research methodology was adopted involving three large Japanese Multinational Corporations and their respective international manufacturing supply networks comprising 19 factories in six countries. The findings suggest that a systematic ramp-up process is crucial to guide manufacturing operations in attaining a predictable initial production yield and rapid production volume ramp-up (time-to-volume). An empirically-based conceptual framework is then developed proposing linkages between critical elements within a manufacturing supply network and operational activities for a new product ramp-up. A structured ramp-up process is then proposed and pilot tested.

Beyond the service factory: Service innovation in manufacturing supply networks

This paper is concerned with the nature of the connection between services and manufacturing in manufacturing-oriented supply networks. The existing literature on manufacturing shifting into service is reviewed and, although such moves are seen as a way to increased revenue and profit, there are concerns that firms do not understand how the capabilities that underpin manufacturing may be extended to enable effective service delivery. Inspired by Chase's concept of the ‘service factory’, which sees the factory as a repository of knowledge and a platform for services, the paper applies Edith Penrose's conception of services as emanating from firms' resources to examine an advanced component manufacturing firm in the course of a number of service-oriented projects. This leads to a model of service development in manufacturing firms, consisting of a network trigger, an opportunity to change the ‘productive opportunity’, the ‘revelation’ of resources and Penrose-services, a reconfiguration of the network, leading to an expanded productive opportunity and hence a platform for marketing new service capabilities. In this sense a network is seen as an inter-connected set of productive opportunities. It also draws attention to the importance in theory and practice of understanding both the institutional and the ontological connection between service offerings and the products, factories, firms and networks with which they are associated.

Knowledge Base Development in Virtual Enterprise Network as Support for Workplace Risk Assessment

The article presents research results based on the concept of collaborative infrastructure (as the virtual enterprise network PREMINV e-platform from “Politehnica” University of Bucharest, Romania), in order to unify existing standards for supply chain management and to provide support in various decision making processes in manufacturing supply networks. The intent is to facilitate and enhance the required knowledge management processes linked with the business process management. The virtual enterprise network expects to reduce small and medium-sized enterprises involvement in networking efforts, enable better and faster decision processes and promote the development of the business services. In addition, the new product development paradigm requires software tools for risk estimation and assessment. For this purpose, the authors describe a knowledge bases method build and use for the professional risk assessment as part of risk management process. The risk level is established based on the probability and severity of its consequences.

Global supply chain control systems: a conceptual framework for the global control centre

The operation of global supply chains is challenging due to the complexity in product and information flows, diversity in sites, localisation and processes and the information processing needed for coordination and control. In order to be competitive, manufacturing supply networks should strive to use information to create transparent and visible demand patterns and to create an efficient balance of supply and demand by an integrated and coordinated manufacturing planning and control system. In this article, a framework for developing global control centres (GCCs) is presented that includes a global control model, performance measurement system, information and communications technology (ICT) and organisation of roles and responsibilities. The framework has been further tested in a company for realising a GCC. The main challenges for realisation include control issues, information handling and ICT and management of change and organisational resistance.

A PROPOSAL ON AGENT-BASED PRODUCTION PLANNING IN INTEGRATED SUPPLY NETWORK

We propose models that focus on the improvement of flexibility in manufacturing supply networks by enabling a tighter information coupling between the various planning levels without tampering with the autonomy of enterprises which are geographically distributed. The problem is approached from the perspective of social network planning using a community of agents. These agents have unique properties which they exhibit at different planning levels. Characterization of agents in the models is discussed.