Agility of Supply Chain Management Solution Using Neural-Fuzzy Approach

2019 ◽  
Vol 16 (10) ◽  
pp. 4143-4148 ◽  
Author(s):  
Avinash Sharma ◽  
Aarti M. Karande ◽  
Dhananjay R. Kalbande
Keyword(s):  
Supply Chain ◽  
Business Process ◽  
Intelligent System ◽  
Business Environment ◽  
Rule Base ◽  
Fuzzy Approach ◽  
Computing Technique ◽  
Neuro Fuzzy ◽  
Soft Computing Technique ◽  
Unpredictable Environment

Enterprise solution is the architecture of collecting and processing business information. Business process agility affects process-based applications works as per changing business environment. This paper helps to understand different changing environment of business process in the supply chain domain. Changes depend on organizational policy; hence it can be incomplete or uncertain. To manage this unpredictable environment, a soft computing technique is used for constructing intelligent system. This paper shows use of Neuro-fuzzy approach to monitor agile behavior of the business process. Neural network phase is used for finding business process and parameter criticality. Fuzzy logic rule base phase calculates process agility based on the relation between process and it’s affecting parameter. Developed tool, shows that business architecture level is more prone to changes as compared to other architectural levels from the enterprise solution.

Evaluating the Operations of an LNG Shipping Company with Business Process Modelling

2021 ◽  
Author(s):  
George O. Andreadis ◽  
Christos Papaleonidas ◽  
Dimitrios V. Lyridis
Keyword(s):  
Supply Chain ◽  
Business Process ◽  
Business Models ◽  
Business Environment ◽  
Process Modelling ◽  
Added Value ◽  
Business Process Modelling ◽  
Holistic View ◽  
Efficient Operation ◽  
Shipping Company

Liquefied Natural Gas (LNG) industry is a typical example for which various business models, strategies, and affiliated interests exist, making it highly complex in terms of operations. The extended supply chain, from liquefaction to regasification, combined with multilateral contractual relationships that crossover, make efficient operation a challenging task. Considering barriers such as the volume of transactions, communication hurdles, etc., and the lack of contemporary management tools by shipping companies contrary to other industries, the paper proposes a model structure based on Business Process Modelling (BPM). The proposed BPM concept offers a holistic view of company organization and operations, as well as enables control of key performance indicators. Implementing intelligent computer systems to model an inter-organizational business environment to highlight and overcome such problems, is the ultimate goal of the study. This paper offers a coherent perspective of business process visualization across the midstream section of the LNG supply chain, including roles, tasks and resources. The research highlights commonly used business models, the contractual framework, and the physical processes. The volume of the information leads to knuckle points and dysfunctions related to time, transparency and work assignment. It is underlined that the occurring issues relate to the nature of LNG projects, business policies, safety and compliance issues, document transaction load and mishandling, disputes over SPAs, as well as to subjects of goodwill and partnership, unstandardized procedures executed empirically, and concurring office intervention. The aim of the study is the identification of the aforementioned problems that prevent an LNG shipping company from extracting the added value from its operation.

scholarly journals Identification of the Critical Factors for Global Supply Chain Management under the COVID-19 Outbreak via a Fusion Intelligent Decision Support System

Axioms ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 61
Author(s):  
Kuang-Hua Hu ◽  
Fu-Hsiang Chen ◽  
Ming-Fu Hsu ◽  
Shuyi Yao ◽  
Ming-Chin Hung
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Rough Set Theory ◽  
Intelligent System ◽  
Multiple Criteria Decision Making ◽  
Business Environment ◽  
Raw Material ◽  
Chain Management ◽  
Past Experiences ◽  
Intelligent Decision Support

Under the ravages of COVID-19, global supply chains have encountered unprecedented disruptions. Past experiences cannot fully explain the situations nor provide any suitable responses to these fatal shocks on supply chain management (SCM), especially in todays’ highly intertwined/globalized business environment. This research thus revisits and rechecks the crucial components for global SCM during such special periods, and the basic essence of such management covers numerous perspectives that can be categorized into a multiple criteria decision making (MCDM) approach. To handle this complex issue appropriately, one can introduce a fusion intelligent system that involves data envelopment analysis (DEA), rough set theory (RST), and MCDM to understand the reality of the analyzed problem in a faster and better manner. Based on the empirical results, we rank the priorities in order as cash management and information (D), raw material supply (B), global management strategy (C), and productivity and logistics (A) for improvement in SCM. This finding is confirmed by companies now undergoing a downsizing strategy in order to survive in this harsh business environment.

scholarly journals Key Performance Indicators On Supply Chain Performance Measurement In An Electronic Commerce: A Literature Review

2019 ◽  
Vol 8 (5C) ◽  
pp. 137-141
Keyword(s):  
Supply Chain ◽  
Performance Measurement ◽  
Electronic Commerce ◽  
Business Process ◽  
Performance Indicators ◽  
Key Performance Indicators ◽  
Business Environment ◽  
Literature Study ◽  
Measurement Models ◽  
Information And Communication

Based on the information and communication technology revolution are characterized by Internet usage in various fields, the business environment also does changing by applying the concept of Electronic Commerce (e-commerce) on its process. Like business activities in general, e-commerce also requires the involvement of various parties, which are referred to Supply Chain Management (SCM). The challenge is while the Supply Chain (SC) performance measurement, that generally conducted in the company with non e-commerce, applied on ecommerce business process. Otherwise, only a few literature studies discuss partially dimension of performance measurement in e-commerce. Therefore, it is important to conduct a literature study about key performance indicators (KPIs) for measuring SC performance in e-commerce dimensions, and it would be explained in this paper. The contribution of this paper proposed the KPIs' that could be used for measuring SC performance in an e-commerce business process in order to be a new approach on the development of SC performance measurement models.

scholarly journals A Soft Computing Platform for Minimizing The Bullwhip Effect

2013 ◽  
pp. 286-293
Author(s):  
Priyadarshini Mishra ◽  
Priti Ranjan Mohanty ◽  
Shashank Mouli Satapathy
Keyword(s):  
Fuzzy Logic ◽  
Supply Chain ◽  
Soft Computing ◽  
Bullwhip Effect ◽  
Intelligent Support ◽  
Computing Technique ◽  
Computing Platform ◽  
Soft Computing Technique ◽  
Fuzzy Logic Technique ◽  
Share Information

An unmanaged supply chain is not inherently stable. The bullwhip effect occurs when the demand order variability’s in the supply chain are amplified as they moved up the supply chain. Distorted information from one end of a supply chain to the other can lead to tremendous inefficiencies. In this paper it is shown that if the members of the supply chain share information with intelligent support technology, and agree on better and better soft computing technique on future sales for the upcoming period, then the bullwhip effect can be significantly reduced. This paper emphasizes on fuzzy logic technique and discusses its effect on reducing bullwhip effect. It is shown that with the application of the fuzzy logic, the multi-objective problems converted to a single one, which can be easily solved with the proposed methodology. It is also shown that linguistic values can be determined to assess vendors’ characteristics, in order to address, in an accurate way.

scholarly journals Weather Modeling Using Data-Driven Adaptive Rough-Neuro-Fuzzy Approach

2017 ◽  
Vol 12 (2) ◽  
pp. 429-435
Author(s):  
M. Sudha
Keyword(s):  
Intelligent Systems ◽  
Prediction Accuracy ◽  
Intelligent System ◽  
Data Driven ◽  
Fuzzy Approach ◽  
Neuro Fuzzy ◽  
Proposed Model ◽  
Hybrid Data ◽  
Weather Modeling ◽  
Using Data

Recently, hybrid data-driven models have become appropriate predictive patterns in various hydrological forecast scenarios. Especially, meteorology has witnessed that there is a need for a much better approach to handle weather-related parameters intelligently. To handle this challenging issue, this research intends to apply the fuzzy and ANN theories for developing hybridized adaptive rough-neuro-fuzzy intelligent system. . Assimilating the features of ANN and FIS has attracted the rising attention of researchers due to the growing requisite of adaptive intelligent systems to solve the real world requirements. The proposed model is capable of handling soft rule boundaries and linguistic variables to improve the prediction accuracy. The adaptive rough-neuro-fuzzy approach attained an enhanced prediction accuracy of 95.49 % and outperformed the existing techniques.

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