A Complexity Model for Assembly Supply Chains and Its Application to Configuration Design

2010 ◽  
Vol 132 (2) ◽  
Author(s):  
Hui Wang ◽  
Jeonghan Ko ◽  
Xiaowei Zhu ◽  
S. Jack Hu
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Product Variety ◽  
Chain Structure ◽  
Complexity Measure ◽  
Supply Chain Configuration ◽  
Supply Chain Structure ◽  
Definition Of ◽  
Optimal Assembly ◽  
Chain Configuration

A complexity measure for assembly supply chains has been proposed based on Shannon’s information entropy. This paper extends the definition of such a measure by incorporating the detailed information of the supply chain structure, the number of variants offered by each node in the supply chain, and the mix ratios of the variants at each node. The complexity measure is then applied to finding the optimal assembly supply chain configuration given the number of variants offered at the final assembler and the mix ratios of these variants. The optimal assembly supply chain configuration is theoretically studied in two special scenarios: (1) there is only one dominant variant among all the variants offered by the final assembler, and (2) demand shares are equal across all variants at the final assembler. It is shown that in the first scenario where one variant dominates the demand, the optimal assembly supply chain should be nonmodular; but in the scenario of equal demand shares, a modular supply chain is better than nonmodular one when the product variety is high. Finally a methodology is developed to find the optimal supply chain with/without assembly sequence constraints for general demands.

Information Sharing Strategies in Business-to-Business E-Hubs

2012 ◽  
pp. 72-93
Author(s):  
Yifeng Zhang ◽  
Siddhartha Bhattacharyya
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Information Sharing ◽  
Chain Structure ◽  
Agent Based ◽  
Key Factor ◽  
Supply Chain Structure ◽  
Hub Model ◽  
Business To Business ◽  
Practical Implications

Studies show that supply chain structure is a key factor affecting information sharing. Business-to-business (B2B) e-hubs have fundamentally changed many companies’ supply chain structure, from a one-to-many to a many-to-many configuration. Traditional supply chains typically center around one company, which interacts with multiple suppliers or customers, forming a one-to-many structure. B2B e-hubs, on the contrary, usually connect many buyers and sellers together, without being dominated by a single company, thus forming a many-to-many configuration. Information sharing in traditional supply chains has been studied extensively, but little attention has been paid to the same in B2B e-hubs. In this study, the authors identified and examined five information sharing strategies in B2B e-hubs. Agent performances under different information sharing strategies were measured and analyzed using an agent-based e-hub model and practical implications were discussed.

Global Product Family Design: A Mathematical Model for Simultaneous Decision of Module Commonalization and Supply Chain Configuration

2011 ◽  
Author(s):  
Kikuo Fujita ◽  
Hirofumi Amaya ◽  
Ryota Akai
Keyword(s):  
Mathematical Model ◽  
Supply Chain ◽  
Product Family ◽  
Product Variety ◽  
Optimization Method ◽  
Product Family Design ◽  
Design Production ◽  
Supply Chain Configuration ◽  
The Given ◽  
Chain Configuration

Today’s manufacturing has become global at all aspects of marketing, design, production, distribution, etc. While product family design has been an essential viewpoint for meeting with the demand for product variety, its meaning is becoming more broad and complicated with linking product design with issues on market systems, supply chain, etc. This paper calls such a design situation ‘global product family design,’ and firstly characterizes its components and complexity. Following them, this paper develops a mathematical model for the simultaneous decision problem of module commonalization strategies under the given product architecture and supply chain configuration through selection of manufacturing sites for module production, assembly and final distribution as an instance of the problems. This paper demonstrates some numerical case studies for ascertaining the validity and promise of the developed mathematical model with an optimization method configured with a genetic algorithm and a simplex method. Finally, it concludes with some discussion on future works.

Complexity Analysis of Assembly Supply Chain Configurations

2008 ◽  
Author(s):  
Hui Wang ◽  
Xiaowei Zhu ◽  
S. Jack Hu ◽  
Yoram Koren
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Mass Customization ◽  
Analytical Study ◽  
Complexity Analysis ◽  
Product Variety ◽  
Entropy Theory ◽  
Modular Assembly ◽  
Supply Chain Configuration ◽  
Assembly Constraints

This paper studies the complexity of assembly supply chains in mass customization environment. The high product variety from mass customization increases the complexity of assembly supply chains. The paper identifies the factors causing supply chain complexity and defines a complexity measure of an assembly supply chain based on these factors and the information entropy theory. Algorithms that determine the optimal supply chain configuration are developed to minimize the supply chain complexity (without and with assembly constraints). This analytical study of supply chain complexity will generate new insights on the influence of product variety on supply chains performance in mass customization. The model and algorithms developed in this paper can assist in making decisions such as when and how to implement a modular assembly supply chain and how much variety should be economically offered.

The “snowball effect” in the transmission of disruptions in supply chains

2016 ◽  
Vol 27 (3) ◽  
pp. 1002-1038 ◽  
Author(s):  
Artur Swierczek
Keyword(s):  
Risk Factors ◽  
Supply Chain ◽  
Supply Chains ◽  
Chain Structure ◽  
Supply Chain Integration ◽  
Negative Consequences ◽  
Content Type ◽  
External Risk ◽  
Supply Chain Structure ◽  
Snowball Effect

Purpose The purpose of this paper is to explore the link between interorganizational integration with respect to its intensity and span, as well as the propagation and amplification of disruptions alongside a supply chain. Design/methodology/approach The paper opted for an exploratory study using a survey of companies. In order to extract the constructs manifesting the span and intensity of integration between companies in supply chains, the principal component analysis was employed. The obtained factor scores were then used as classification criteria in the cluster analysis. It enabled to include similar organizations in terms of intensity and span of supply chain integration. In order to validate the obtained results, the analysis of variance (ANOVA) was conducted and regression models were developed. Findings The findings of the study show that there is a relationship between the intensity and span of supply chain integration and the “snowball effect” in the transmission of disruptions. The obtained findings show that the span of supply chain integration is negatively associated with the strength of the “snowball effect” in the transmission of disruptions. In addition, the results suggest that more intense supply chain integration contributes to the “snowball effect” in material flows in the forward and backward transmission of disruptions. Research limitations/implications Although the current study investigates the intensity and span of integration within the basic, extended and ultimate supply chain structure, it still lacks the broader analysis of the “snowball effect” in the transmission of disruptions. The study investigates this phenomenon only within the basic supply chain structure, constituted by the primary members. Another challenge is to examine if the effects of external risk factors (e.g. natural disasters) may also be transferred to other links in the supply chain structure, and what are the similarities and differences (if any) between the mechanism of propagation and amplification of disruptions elicited by internal and external risk factors. Another future direction of study is to define other ways of identification and measurement of the “snowball effect” in order to make cross-industrial and international comparisons of disruptions amplified in the transmission more standardized and objective. In the current study, the phenomenon of the “snowball effect” is anchored in the subjective opinions of managers who may view the problem from different angles. Consequently, the study is limited to individual perceptions of the strength of disruptions affecting the solicited company, its customers and suppliers. Practical implications In practical terms, the findings provide crucial information for the framework of supply chain risk management and therefore enable its more efficient and effective implementation. The better the managers understand the nature of the “snowball effect” in the transmission of disruptions, the easier it is for them to allocate resources and apply necessary managerial tools to mitigate the negative consequences of risk more effectively. The deliverables of the study also confirm that the interorganizational exchange of information accompanying the supply chain integration enables to mitigate the strength of the “snowball effect” in the transmission of disruptions. Another important implication is the broadening of practical expertise concerning the use of integration not only as a means of obtaining and sustaining supply chain effectiveness and efficiency, but also as the way to mitigate the “snowball effect” in the transmission of disruptions. Therefore, nowadays the supply chain managers are facing another challenging task – namely, how to balance supply chain integration in terms of span and intensity to ensure profits from integration and mitigate the negative risk consequences transmitted among the links in supply chains. Originality/value The paper elaborates on the underestimated issue of the “snowball effect” in the transmission of disruptions and its drivers. In particular, the paper attempts at filling the gap in empirical studies concerning the relationships between the “snowball effect” in the transmission of disruptions and supply chain integration.

Supply Chain Structure and Competitor Relationship

2020 ◽  
Author(s):  
Jing Wu ◽  
Yang Xu
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Theoretical Basis ◽  
Chain Structure ◽  
Shock Propagation ◽  
Supply Chain Network ◽  
Empirical Methods ◽  
Competition Intensity ◽  
Cross Border ◽  
Supply Chain Structure

This chapter discusses recent relevant empirical research using the supply chain structure observed in the actual data, including shock propagation in the supply chain network, social capital, and supply chains, and cross-border supply chains. It also introduces some commonly used empirical methods and databases, and provides the corresponding financial theoretical basis for the conclusions of these studies. Finally, the chapter suggests a new angle to fully utilize the supply chain structure to identify the competitor relationship and the competition intensity. The chapter indicates that higher supply chain overlap increases the correlation of the competitors’ economic performance, suggesting that sharing supply chains reduce competition. This conclusion is helpful for entrepreneurs to better manage firm competitions.

Layer analysis of CO2 sources in the US economic supply chains: an input output LCA study

2017 ◽  
Vol 117 (10) ◽  
pp. 2171-2193 ◽  
Author(s):  
Gokhan Egilmez ◽  
N. Muhammad Aslaam Mohamed Abdul Ghani ◽  
Ridvan Gedik
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Carbon Footprint ◽  
Sustainability Assessment ◽  
Chain Structure ◽  
Total Carbon ◽  
Input Output ◽  
Content Type ◽  
The Us ◽  
Supply Chain Structure

Purpose Carbon footprint assessment requires a holistic approach, where all possible lifecycle stages of products from raw material extraction to the end of life are considered. The purpose of this paper is to develop an analytical sustainability assessment framework to assess the carbon footprint of US economic supply chains from two perspectives: supply chain layers (tiers) and carbon footprint sources. Design/methodology/approach The methodology consists of two phases. In the first phase, the data were collected from EORA input output and environmental impact assessment database. In the second phase, 48 input-output-based lifecycle assessment models were developed (seven CO2 sources and total CO2 impact, and six supply chain tiers). In the third phase, the results are analyzed by using data visualization, data analytics, and statistical approaches in order to identify the heavy carbon emitter industries and their percentage shares in the supply chains by each layer and the CO2 source. Findings Vast majority of carbon footprint was found to be attributed to the power generation, petroleum refineries, used and secondhand goods, natural gas distribution, scrap, and truck transportation. These industries dominated the entire supply chain structure and found to be the top drivers in all six layers. Practical implications This study decomposes the sources of the total carbon footprint of US economic supply chains into six layers and assesses the percentage contribution of each sector in each layer. Thus, it paves the way for quantifying the carbon footprint of each layer in today’s complex supply chain structure and highlights the importance of handling CO2 source in each layer separately while maintaining a holistic focus on the overall carbon footprint impacts in the big picture. In practice, one size fits all type of policy making may not be as effective as it could be expected. Originality/value This paper provides a two-dimensional viewpoint for tracing/analyzing carbon footprint across a national economy. In the first dimension, the national economic system is divided into six layers. In the second dimension, carbon footprint analysis is performed considering specific CO2 sources, including energy production, solvent, cement and minerals, agricultural burning, natural decay, and waste. Thus, this paper contributes to the state-of-art sustainability assessment by providing a comprehensive overview of CO2 sources in the US economic supply chains.

Build Structure of Fractal Interorganizational Information Systems and Optimize Supply Chain Structure

2012 ◽  
Vol 468-471 ◽  
pp. 268-276
Author(s):  
Wei Qing Zhuang ◽  
Zhen Yu Liu
Keyword(s):  
Supply Chain ◽  
Information Systems ◽  
Fractal Theory ◽  
Chain Structure ◽  
Interorganizational Information Systems ◽  
Self Similarity ◽  
Fractal Characteristics ◽  
Supply Chain Structure ◽  
Definition Of ◽  
Dla Model

This paper uses fractal theory to analyze interorganizational information systems (IOS). Firstly, IOS’s structure has fractal characteristics of self-similarity, self-optimization and self-organization, consequently, gives the concept and definition of fractal interorganizational information systems (FIOS). Thirdly, builds IOS topological structure fits actual needs based on Diffused-Limited Aggregation (DLA) model to optimize the growth rule of IOS, then, designs six topological structures of FIOS and estimates approximatively their fractal dimension values. Finally, gives fractal interorganizational information systems application to optimize the supply chain network structure to improve operation efficiency.

Supply Chain Management under Mass Customization

2012 ◽  
Vol 616-618 ◽  
pp. 2044-2047 ◽  
Author(s):  
Li Liu
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Mass Customization ◽  
Mass Production ◽  
Chain Structure ◽  
Network Structures ◽  
Chain Management ◽  
Open Network ◽  
Supply Chain Structure ◽  
Definition Of

Traditional supply chain is established on mass production while supply chain under mass customization is established on mass customization. In the paper, Definition of Supply Chain Management is introduced; Comparison between Traditional Supply Chain and Supply Chain under Mass Customization, State of the field are all illustrated. Under mass customization, in order to adapt to customer driving manufacturing and the demands of enterprise alliance, manufacturers and major enterprises will directly contact with customers to weaken or even eliminate the function of distributors and retail dealers, which will lead to the transformation of the supply chain structure to open network structures made up of suppliers, manufacturers, core enterprises and customers.

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