Analysis of Decision Models in Supply Chain Management

Venugopalan, Jivanath; Sarath, V.S.; Pillai, Roshan Jayaraj; Krishnan, S.; Anbuudayasankar, S.P.

doi:10.1016/j.proeng.2014.12.470

Cited by 8 publications

(2 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…2.2.1. Categorical model In the categorical model (Willis & Houston, 1990;Zhu, 2008;Venugopalan, Sarath, Pillai, Krishnan, & Anbuudayasankar, 2014), suppliers are evaluated by criteria such as cost, quality, speed of delivery, etc. With regard to each criterion, suppliers are classified as good, fair, poor and assigned a (þ), (0) or (À) for each level, respectively.…”

Section: Review Of the Supplier Selection Methodsmentioning

confidence: 99%

L.A.R.G. supplier selection based on integrating house of quality, Taguchi loss function and M.O.P.A.

Zanjirani

Zolfani

Prentkovskis

2019

Economic Research-Ekonomska Istraživanja

View full text Add to dashboard Cite

show abstract

Section: Review Of the Supplier Selection Methodsmentioning

confidence: 99%

L.A.R.G. supplier selection based on integrating house of quality, Taguchi loss function and M.O.P.A.

Zanjirani

Zolfani

Prentkovskis

2019

Economic Research-Ekonomska Istraživanja

View full text Add to dashboard Cite

show abstract

“…The supply chain business process can be seen from two perspectives: the cycle view and the push or pull view, as described by [12]. Supply chain processes have a major influence on global business and trade [13]. Supply chain management plays a very important role in a business process [14].…”

Section: Business Process Relations Of Supply Chainmentioning

confidence: 99%

Business Process of Red Chili Supply Chain Based on Food Supply Chain Network in Yogyakarta Indonesia

Susanawati,

Delliviana Rismayanti,

Akhmadi

2023

E3S Web of Conf.

View full text Add to dashboard Cite

Red chili is one of the horticultural crops that has a selling value for farmers. However, the distribution system is an inhibiting factor in farmers’ income. This study aims to analyze the red chili supply chain and business process from the production center in Yogyakarta to consumers in Jakarta, Indonesia. Kulon Progo Regency served as the study’s primary location. The sampling for this study was conducted in stages. A total of 80 farmers were selected purposively as the sample. From farmers to consumers in Jakarta, 67 supply chain actors were gathered using snowball sampling. The Food Supply Chain Network (FSCN) model was employed to structure the data analysis. According to the findings, eight actors and three distinct chains were involved in the red chili supply chain. The product and money flow across the three chains ran smoothly; however, the information flow did not. Both three-cycle and push or pull views made up the business process relationship, with all three chains being in the same state. Nine supporting actors were involved in the red chili supply chain, and several agencies and educational institutions performed collaborative studies. The chain actors were exposed to six risks, and no brands were associated with the distributed products. The contract did not formally bind cooperation along the supply chain.

show abstract

3D Visualization System of Manufacturing Big Data and Simulation Results of Production for an Automotive Parts Supplier

Hwang

Noh

2019

IFIP Advances in Information and Communication Technology

View full text Add to dashboard Cite

Recently, many manufacturers have recalled their products owing to quality issues. It is increasingly difficult to determine the cause of quality issues because of the complexity of the supply chain. Thus, it is essential to share manufacturing information throughout the product life cycle. However, small and medium-sized enterprises (SMEs) often lack the necessary infrastructure and information systems. This research proposes an open-source system allowing the 3D visualization of production history and simulation results. The production history includes products' time stamps and inspection results, defect information, and a status of each facility. This information is then used to construct a product workflow and simulation model. Further, it is possible to compare simulation results for up to three alternative scenarios. The system is developed using open-source libraries for easy diffusion and application to SMEs in the automobile industry. A method for the implementation of this system to Korean auto parts companies is introduced.

show abstract

Analysis of Decision Models in Supply Chain Management

Cited by 8 publications

References 20 publications

L.A.R.G. supplier selection based on integrating house of quality, Taguchi loss function and M.O.P.A.

L.A.R.G. supplier selection based on integrating house of quality, Taguchi loss function and M.O.P.A.

Business Process of Red Chili Supply Chain Based on Food Supply Chain Network in Yogyakarta Indonesia

3D Visualization System of Manufacturing Big Data and Simulation Results of Production for an Automotive Parts Supplier

Contact Info

Product

Resources

About