Part Of Supply Chain Management Research Articles

Investigating the Impact of 4IR Technologies on Supply Chain Performance: A Literature Review

Supply chain performance measurement is an integral part of supply chain management that reveals the efficiency, health and success of the supply chain and offers areas for improvement in this regard. Nowadays, new ways maintain to be sought to realise the highest possible potential of supply chains. The Fourth Industrial Revolution enabled limitless benefits to supply chains and created a transformation that alters the entire supply chain and business models. This study aims to reveal the contributions of this industrial revolution’s technologies to supply chain performance and to ensure superior performance is achieved thanks to these technologies. In this study, the fourth industrial revolution was examined in light of the stages of industrial revolutions and the concept of supply chain performance was explained by considering the historical development of performance management. Afterwards, the dimensions of supply chain performance in the literature and the SCOR model version 13.0 attributes and their metrics, which are considered as dimensions of supply chain performance in this study, are elaborated. The contributions of these technologies to supply chain performance were investigated. The study ended with the evaluation of the findings.

Prediction of the process capability for compression rubber part forming in the automotive supply chain

The paper proposes predicting production process capability for the compression rubber part in automotive supply chain management. Delivery of parts to tier 1 and OEM on time is the most important part of supply chain management, together with the delivery of on-quality and on-cost control to maintain the competitiveness of the supply chain. There are many suppliers to produce many automotive parts for tier 1. Therefore, the simulation approach properly predicts and prevents the process from getting into trouble during the actual production time. Production process quality control is critical to ensure that the good quality of the parts purchased can be delivered on time. Rubber parts are used widely in automotive, motorcycles, trucks, and other types of vehicles, with small sizes but in huge quantities to support general OEM brands and specific parts. The rubber part manufacturing process is complex and uncertain with compression moulding and rubber curing conditions. Therefore, good conditions can predict the production process's capability to commission and deliver on schedule.A neuro-fuzzy system is adopted and developed to deal with the uncertain process capability under multi-criteria decision-making.The methodology development can be used in the actual rubber part manufacturing supply chain environment and can predict uncertain problems that might occur in the subcontractor factories.The prediction of the production process capability of the rubber part supply chain might be more effective on the real-time monitoring control system and can be tracking location part progress for further planning both success or rescheduling.The platform can be applied to audit and test the actual industrial supply chain, and problem and research questions are brought about from the real supply chain in the local country.The methodology development was originally created for the particular supply chain in rubber automotive parts that can replace the existing system to obtain a more efficient performance evaluation process.

Evaluation of critical success determinants to the implementation of additive manufacturing technology in the spare parts supply chain: a grey causal modelling approach

PurposeAdditive Manufacturing technology (AMT) is swiftly gaining prominence to induce automation and innovation in manufacturing systems. It holds immense potential to change supply chain dynamics by providing the possibility of printing objects on demand. This study thus formulates and analyzes the framework to incorporate AMT to handle the spare parts supply chain management (SPSCM) in capital-intensive industries by identifying and assessing the critical success factors (CSFs).Design/methodology/approachAssessment of the CSFs is performed using the novel Grey Causal Modeling method (GCM) with the objective of making SPSCM resilient and efficient. GCM conducts causal analysis by taking into consideration cause, effects, the objectives, and the situations.FindingsFindings indicate that; Logistics Lead Time (SD4), Time to manufacture (SD3), Management Support (SD11), and Risk Management (SD20) are the most prominent causal factor having a maximum impact when incorporating AMT in SPSCM. The results also reveal that the performance of manufacturing organizations that adopt AMT is substantially influenced by internal and external factors such as Management Support (SD11) and Government Regulations (SD16).Research limitations/implicationsThis research provides valuable information for getting the global spare parts supply chain equipped for the post-COVID age, where digital technologies such as AMT will be fundamental for bolstering supply chain resilience and efficiency.Originality/valueThis research proposes a framework for performance assessment when incorporating AMT in SPSCM. Study also demonstrates methodological application of novel Grey Causal Modelling technique using a real case in a spare parts manufacturing industry in India.

A digital twin-enabled digital spare parts supply chain

An efficient and effective spare parts supply chain management is crucial to ensure highly available production systems. However, achieving such a spare parts supply chain management is challenging due to the intrinsic characteristics of spare parts. Traditional spare parts supply chains (TSPSCs) adopt large spare parts inventories to tackle such intrinsic characteristics, with disadvantages in terms of high inventory costs. Recently, Additive Manufacturing (AM) has shown breakthrough potential, allowing the transition from TSPSCs to digital spare parts supply chains (DSPSCs), where spare parts are no longer stored in large amounts but are stored digitally and produced only when needed. However, despite DSPSCs benefits, a complete transition from TSPSCs to DSPSCs is still far from becoming reality. Indeed, hindering such a transition is a lack of expertise in three main areas, i.e. how to design, operate, and control and monitor a DSPSC. With this position paper, we envision how a digital twin (DT) could overcome these issues, enabling a full transition to a DSPSC. Moreover, this work further concretely suggests how such a DT could be developed, providing the basis for developing both the theoretical and practical knowledge necessary to render DSPSCs a reality.

Inventory Model for Deteriorating Pharmaceutical Items with Linear Demand Rate

Good management of goods is needed so that the inventory activities of a business can run smoothly as the part of supply chain management which aims to monitor the flow of stock of goods from the purchasing process, and storage to the point of sale. In terms of inventory or supplies of pharmaceutical goods, conditions such as shortages or stockouts must also be considered which are a matter of control, management, and security. In this study, an inventory model is formulated with deterioration or damage to pharmaceutical goods that occurs due to the length of time when the goods are stored with a linear demand level. In the optimal solution, the inventory time occurs when it reaches the zero point (t1) of 0.34 and the cycle length (T1) of 0.83 with an average minimum total cost (TC) of $445.25 per cycle which is completed by WolframAlpha software. Sensitivity analysis changes the value results in the value of (TC) which that increases for all parameters. In increasing the linear function variables (a and b), it produces t1 and T1 stable values. An increase in the cost of each item damage (DC) and constant damage rate (theta) produces a t1 stable value, but the value of T1 increases. The increase in storage costs (h) results in a decrease in the value of t1 and T1. An increase in the cost of shortages (s) results in an increase in the value of t1 and a decrease in the value of T1.

Data-Driven Decision Making in Supply Chain Management

The importance of making decisions in supply chain management (SCM) based on data has grown significantly in recent years due to the quickly changing nature of the modern corporate environment. Within the scope of this abstract, the transformational influence of data analytics on supply chain management is investigated. Particular attention is paid to the ways in which data-driven strategies improve decision-making processes, increase operational efficiency, and boost competitive advantage. The coordination of a number of operations, including as distribution, manufacturing, inventory management, and procurement, is an essential part of supply chain management. In the past, these processes were handled by the use of intuition and facts from the past. But the introduction of sophisticated data analytics tools has completely changed the way that this approach is taken. Organisations are able to improve their operations, acquire deeper insights into the dynamics of their supply chains, and more correctly estimate demand when they make use of real-time data, predictive analytics, and machine learning algorithms.

AN ASSESSMENT OF CHALLENGES AND FACTOR INFLUENCING THE FREIGHT FORWARDING BUSINESS IN THE LOGISTICS INDUSTRY

This research was undertaken with the sole aim of understanding some of the challenges and Factor Influencing the Freight Forwarding Business in the organizations involved the Forwarding and distribution of shipper Cargo encounter in their logistics operations. A freight forwarder is a person or company that organizes shipments for individuals or corporations to get large orders from the manufacturer or producer to market or final point of distribution. Forwarders will contract with a carrier to facilitate the movement of goods. A forwarder is not typically a carrier but is an expert in supply chain management. In other words, a freight forwarder is a "travel agent," for the cargo industry, or a third-party (non-asset-based) logistics provider. A forwarder will contract with asset- based carriers to move cargo ranging from raw agricultural products to manufactured goods. The term Logistics Management or supply chain management is that part of Supply Chain Management that plans, implements, and controls the efficient, effective, forward, and reverse flow and storage of goods, services, and related information between the point of origin and the point of consumption in order to meet customer's requirements. The research targeted a selected sample of Employees and representatives of transporters of goods and key management personnel of Companies Central Distribution Center based in the industrial area Chennai. The primary objective of this project is to conduct ‘A study on Challenges and factor influencing the freight forwarding business in the Freightkare Multimodal Logistics Pvt. ltd. It is important to analyze the problems faced by freight forwarders from the carriers as well as companies and individual customers. By studying and comparing the various problems faced by the freight forwarders. It is easy identifying the solutions to avoid the problems and make sure the smooth flow of business. This will help Freightkare Multimodal Logistics Pvt. ltd to establish a reasonable share in the marketplace.

Rethinking Additive Manufacturing for Spare Parts Supply Chain Management

Overview: Given the ongoing advancements in additive manufacturing (3D printing), many companies are considering using this digital technology for the supply of spare parts. This study identifies the advantages and barriers of additive manufacturing in the context of spare parts supply chain management. The case study examines the perspectives of a manufacturer and a customer of a spare parts supply chain. We present several questions that practitioners can use to (re)consider additive manufacturing for their companies.

Sustainable Supplier Selection using Neutrosophic Multi-Criteria Decision Making Methodology

Sustainable supplier selection is an important part of supply chain management since it encourages ethical and eco-friendly procedures. This study examines the most important criteria and factors for judging the sustainability performance of suppliers and presents a thorough overview of sustainable supplier selection. A decision-making framework for sustainable supplier selection is created via a review of relevant research, case studies, and best practices. Key factors for assessing suppliers include environmental performance, social responsibility, and economic viability, all of which are included in the framework. The results stress the need to take into account suppliers' energy efficiency, waste management, and social responsibility initiatives including fair labor practices and community involvement. Other essential considerations for long-term sustainability include economic viability and supply chain resilience. Organizations may improve their environmental impact, reduce supply chain risks, and boost overall performance by using sustainable supplier selection practices. This study used the TOPSIS method to rank sustainable suppliers. The TOPSIS method is employed with the single-valued neutrosophic set to deal with vague information. A case study in a food company is conducted to show the best supplier

Evaluating and Ranking SCPMS Enablers Using ISM and SWARA

The supply chain performance measurement system (SCPMS) is considered an integral and important part of supply chain management (SCM) for an effective and efficient supply chain (SC). The healthier and more flexible SCPMS is based on the enablers from which the SC metrics are taken. The identification of such enablers must be aligned with the strategic objectives of the organization and mapped to the SC measurement objectives. Hence, this study identifies a set of enablers and ranks them. Interpretive structural modeling (ISM)-based methodology is used in the current study to model the SCPMS implementation enablers. MICMAC analysis is further employed to categorize and comprehend the importance of each SCPMS enabler. ISM offers relationship modeling of SCPMS enablers, whereas MICMAC helps with classifying them into four categories. The Delphi method is then used to validate the ISM model. The SCPMS variable is also used in prioritization using stepwise weight assessment ratio analysis (SWARA). Practicing managers may benefit when developing and installing the SCPMS to satisfy the requirements of supply chain 4.0 for Industry 4.0 (I4.0). They will also be able to recognize and allocate resources while implementing SCPMS. The prioritization using SWARA provides an important ranking according to its importance. The SCPMS enablers of ‘top management support’, ‘SC 4.0 performance measurement awareness’, and ‘managerial readiness’ are found to be significant.

PEMBUATAN APLIKASI JASA PENYEWAAN TRUCK BERBASIS ANDROID (SELVARU TRUCK)

Logistics is an important part of supply chain management and includes activities such as planning, executingand controlling the process of moving goods, storing goods, and managing transportation. In addition, the wordlogistics also refers to the distribution process which is the process of moving products or materials from oneplace to another. One of the implementation of logistics activities and distribution of goods is the activity ofsending goods via land by using trucks as a means of transporting the movement of these goods. The applicationof goods delivery activities using trucks is the availability of truck rental services that facilitate the delivery ofgoods or cargo from one place to another, which is needed by business owners and individuals who need theseservices. And in today's technological era, one of the realizations that supports the truck rental service is theexistence of an application that can make it easier for people to access and use it. The Selvaru Truck applicationis designed as a solution to the problem of shipping goods, namely as a service that provides a fleet of trucks forshipping goods based on Android applications..

SUPPLY CHAIN RISK ANALYSIS AND ASSESSMENT USING ANALYTICAL HIERARCHY PROCESS (AHP): A REVIEW

In these days, increasing consumer demand uncertainties, e.g. due to war in Europe, severe drought in west Europe or Covid pandemic, increase challenge in supply chain operation. Uncertainty and unreliable events interfere supply chain’s operations and strategies. As a result, increasing risks in supply chain becomes vulnerable and leads to undesired circumstance. A systematic approach is therefeore required to manage the risks. Of many methods, supply chain risk management (SCRM), as a part of supply chain management (SCM), is offered in this paper to address this challenge. The SCRM increases supply chain resilience agains many uncertainties. An important key of SCRM is risk assessment as risk-impact ordering method which can deliver solution with the lowest risks. Of many methods applied for risk assessment, analytic hierarchy process (AHP) provides several advantages, e.g. it can be used as multi-criteria decision making, it can be used with high flexibility and it can be used as subjective assessment. This paper discusses the AHP method in supply chain risk assessment as well as offers a new AHP structure applied for risk analysis.

Sustainable Supplier Selection and Evaluation for the Effective Supply Chain Management System

With increased environmental protection awareness, sustainability has been incorporated into supply chain management. Sustainable supplier selection and evaluation have become an acritical part of supply chain management. They can significantly improve the supply chain’s operational performance and enhance enterprises’ competitiveness. Based on trapezoidal interval type-2 fuzzy numbers (TIT2FNs) and cloud probability dominance relations (PDR), manufacturers can make more tangible and environmentally friendly decisions in the SSSE process. In this paper, a SSSE indicator system is first established using the necessary economic, environmental, and social factors. The importance of the indicators described in linguistic terms is transformed into TIT2FNs, and the weight of each indicator is calculated. In order to prevent candidate suppliers from promoting performance maliciously, different weights are given according to the impact of the enterprise’s historical performance on the present. Finally, the cloud PDR method is used to determine the optimal sustainable supplier. A case study and analysis are provided to show the feasibility and superiority of the proposed method.

Risk analysis of shallot upstream supply chain in Malang during COVID-19 pandemic

A sustainable supply scenario becomes an important part of supply chain management for agricultural products in a conjuncture situation. In order to invent sustainable agriculture product supply, it is necessary to ensure that the existing upstream supply chain is sufficiently resilient with minimum disruption. This research aims to analyze risk in the shallot upstream supply chain in Malang during the Covid-19 pandemics. In this study, 8 shallots farmers and 3 intermediaries/traders were interviewed as key informants, and the purposive method was used. Upstream supply chain risk analysis is carried out in two stages to analyze risks from farmers and traders. Analysis was done by using a risk matrix. The result shows that the main risk of sustainable aspects within the upstream level is economic aspects. The distribution level needs to be paid more attention to because it has more risks than the farmers’ level.

A model-experience-driven method for the planning of refined product primary logistics

Logistics planning is regarded as the most complex part of supply chain management for refined products. A vital knowledge gap still exists in understanding the trade-offs between the economy and the practicability of logistics schemes. Focus on this issue, this paper proposes a model-experience-driven method for the planning of refined product primary logistics. The method couples three sub-modules: (1) use coordinator's preference information and convex function interpolation to construct satisfaction indicator; (2) set up a multi-objective model for logistics coordination and optimization considering supply adjustment and secondary delivery; (3) adopt the augmented ɛ-constraint method to obtain the Pareto solutions and balance the economy and satisfaction indicators. The method is verified by a small-scale system, where the satisfaction degree increases by 77% while the logistics cost remains unchanged. The method is also successfully applied to a large-scale system with 29 refineries and 196 market depots, where Pareto logistics schemes are obtained and the supply–demand imbalance is greatly eased. The proposed method can help provide theoretical guidance for real-world logistics planning.

Beauty of Block Chain Technology in Supply Chain Management

Block chain is an innovative device which plays an important part in Supply chain management (SCM). Most importantly, it solves the discernibility issue in the supply chain management. We in the first place introduce a general block chain-based item detectability structure. This system depends on a cross-fringe web based business flexible chain setting. It is a model which combines multi-chain framework model, information board model and square artefact model. A few other techniques and calculations such as data tying down strategy, key dissemination technique, data encryption calculation and hostile to forging technique are additionally used. The structure, models and techniques assessed by applying to a few regular issues. The adequacy, security, execution and administration problems of applying these arrangements are also important and hence addressed in this article.
 HIGHLIGHTS
 
 It resolves the discernibility issue in the supply chain management
 This system depends on a cross-fringe web based business flexible chain setting
 It is a combination of multi-chain framework model, information board model and square artefact model

Mitigating spread of contamination in meat supply chain management using deep learning

Industry 4.0 recommends a paradigm shift from traditional manufacturing to automated industrial practices, especially in different parts of supply chain management. Besides, the Sustainable Development Goal (SDG) 12 underscores the urgency of ensuring a sustainable supply chain with novel technologies including Artificial Intelligence to decrease food loss, which has the potential of mitigating food waste. These new technologies can increase productivity, especially in perishable products of the supply chain by reducing expenses, increasing the accuracy of operations, accelerating processes, and decreasing the carbon footprint of food. Artificial intelligence techniques such as deep learning can be utilized in various sections of meat supply chain management––where highly perishable products like spoiled meat need to be separated from wholesome ones to prevent cross-contamination with food-borne pathogens. Therefore, to automate this process and prevent meat spoilage and/or improve meat shelf life which is crucial to consumer meat preferences and sustainable consumption, a classification model was trained by the DCNN and PSO algorithms with 100% accuracy, which discerns wholesome meat from spoiled ones.

Order picking and loading-dock arrival punctuality performance indicators for supply chain management: A case study

Abstract Supply chain activity control is an essential part of Supply Chain Management (SCM), ensuring compliance with customer requirements. This paper presents a case study into the control of SCM activities. The study analysed two areas involving two different SC links associated with order picking, and outsourced truck freights, respectively. The studied company had problems with these links. An approach based on developing a KPI (Key Performance Indicator) was proposed to address the issues. Consequently, different affected processes were analysed and characterised, considering the relevant data for defining a KPI. Then, strategies and methods were devised for data collection and processing regarding the system’s current state. Finally, tools were designed to facilitate the interpretation of the system’s current state and thus, pave the way for the decision-making process on corrective measures.

A comprehensive literature review on spare parts logistics management in the maritime industry

Supply chain and logistics management for spare parts is of key importance in the maritime industry, in order to ensure high availability and reliability of assets, while keeping operating costs in acceptable levels. Supply chain and logistics operations for spare parts incorporate high complexity, uncertainty and costs, due to special characteristics of the maritime sector, as for instance moving assets, globally scattered points of supply and demand, strict time windows and multi-actor setting. Typically, the asset owner purchases spare parts for their vessel from a foreign supplier, and consolidates them in a regional warehouse. Subsequently, these spare parts are shipped to a port using various means of transport such as air freight, sea freight or road freight. Finally, once the vessel calls at subject port, the spare parts are delivered and used on board for maintenance activities. For repairable items, the reverse logistics process also does exist; a spare part is offloaded from a vessel, repaired and then re-delivered on board. Efficiently handling such a logistics network constitutes a great challenge, nevertheless, this topic has received little attention in the literature and a systematic review is currently missing. In this paper, the authors attempt to address this research gap by performing a systematic literature review on spare parts supply chain and logistics management in the maritime sector. To achieve this objective, after applying the defined inclusion and exclusion criteria on the initial search results, a set of (30) eligible papers, participating in the review, has been identified. These selected papers are illustrated and discussed in detail, with the purpose of addressing the research questions initially set by the authors. Fundamentally, this study aims to describe the current state of the art in the subject area, identify existing challenges and trends, and finally provide suggestions on future research. We aspire that the results of this review can be used as the foundation for future research on spare parts supply chain management in the maritime sector.

CURRENT TRENDS IN THE FIELD OF LOGISTICS MANAGEMENT AT THE ENTERPRISE

In terms of management content, logistics management includes logistics activities and other activities directly related to logistics activities. The content related to supply chain management is more complex. Supply chain management is a model that connects suppliers, manufacturers, distributors and retailers through information feedback. Supply chain management includes business flow management, information flow management, capital and value flow management, and logistics management. Logistics management is part of supply chain management. The purpose of this study is to analyze existing tools and practices for innovation in logistics management in enterprises. Increased competition in the market forces traders to use various methods in order to maintain the profitability of the firm by reducing logistics losses. The main course to reduce logistics losses in trade is considered to be a separate association, which allows the optimal way of goods movement. Integration of logistics between production, transport, wholesale and retail organizations plays a crucial role in trade integration. Research on logistics for a wide range of markets (from food markets to capital-intensive manufacturing) shows that manufacturing companies and intermediaries have ample opportunity to create favorable conditions for consumers. However, these possibilities can only be realized if the logistics operation extends entirely exclusively to the market. In conclusion, it can be argued that the main goal of logistics goes beyond reducing costs and increasing profits. During the development of logistics in industrialized countries, a system of indicators has been formed, in general, to evaluate its effectiveness, efficiency and efficiency. General logistics costs are the total costs associated with the complex functional management and administration of logistics in the logistics system. Common to Western business is the allocation and accounting costs of transportation, warehousing, materials handling, inventory management, order management, information and computer support, and more.