scholarly journals Approach to intellectualization of complete supply chain management processes using fuzzy expert systems

2021 ◽  
pp. 26-39
Author(s):  
Yuri Romanenkov ◽  
◽  
Yashar Rahimi ◽  
Mariia Danova ◽  
Olena Feoktystova ◽  
...  
Keyword(s):  
Decision Making ◽  
Network Model ◽  
Petri Net ◽  
Business Processes ◽  
Resource Constraints ◽  
Raw Materials ◽  
Central Element ◽  
Typical Food ◽  
Upper Level ◽  
Fuzzy Network

”. It is shown that in order to increase the efficiency of the functioning of complete logistical supply chains (CLSC), it is necessary to develop special methodological tools, and, on their basis, software to facilitate decision-making on the timely formation of liquid consignments at the terminal sections of the chain of liquid goods. The article describes a fuzzy network of CLSC in the form of a hierarchical two-level nested Petri net (NPN), the upper level of which reproduces the process of functioning of the focal company as the central element of the CLSC, and each of the components of the lower level of the network model is an elementary Petri net reflecting the logistic processes at the terminal sections of the CLSC production of raw materials and sale of finished products. This article also gives a description of the procedure for creating a fuzzy network model for representing information about business processes that take place during the functioning of the CLSC, taking into account the existing time and resource constraints, in the form of a NPN, which is expanded by introducing fuzzy and temporal statements. Special methods of automated decision- making on the sustainable functioning of CLSCs are described and justified in terms of making a choice on the transport mode and optimal routing. Based on the developed methodological tools, the process of forming and providing the stable functioning of the CLSC for typical food products of the grocery group, namely dried fruits, is considered.

scholarly journals Identification of reverse logistics decision types from mathematical models

2018 ◽  
Vol 11 (2) ◽  
pp. 239 ◽  
Author(s):  
Pascual Cortés Pellicer ◽  
Faustino Alarcón Valero
Keyword(s):  
Decision Making ◽  
Mathematical Models ◽  
Reverse Logistics ◽  
Business Processes ◽  
Raw Materials ◽  
Decision Makers ◽  
Social Awareness ◽  
Decision Variables ◽  
Object Of Study ◽  
Aid Decision

Purpose: The increase in social awareness, politics and environmental regulation, the scarcity of raw materials and the desired “green” image, are some of the reasons that lead companies to decide for implement processes of Reverse Logistics (RL). At the time when incorporate new RL processes as key business processes, new and important decisions need to be made. Identification and knowledge of these decisions, including the information available and the implications for the company or supply chain, will be fundamental for decision-makers to achieve the best results. In the present work, the main types of RL decisions are identified.Design/methodology/approach: This paper is based on the analysis of mathematical models designed as tools to aid decision making in the field of RL. Once the types of interest work to be analyzed are defined, those studies that really deal about the object of study are searched and analyzed. The decision variables that are taken at work are identified and grouped according to the type of decision and, finally, are showed the main types of decisions used in mathematical models developed in the field of RL.    Findings: The principal conclusion of the research is that the most commonly addressed decisions with mathematical models in the field of RL are those related to the network’s configuration, followed by tactical/operative decisions such as the selections of product’s treatments to realize and the policy of returns or prices, among other decisions.Originality/value: The identification of the main decisions types of the reverse logistics will allow the managers of these processes to know and understand them better, while offer an integrated vision of them, favoring the achievement of better results. 

scholarly journals Ontology-driven approach for describing industrial socio-cyberphysical systems’ components

2018 ◽  
Vol 161 ◽  
pp. 03027 ◽  
Author(s):  
Nikolay Teslya ◽  
Igor Ryabchikov
Keyword(s):  
Internet Of Things ◽  
Business Processes ◽  
Raw Materials ◽  
Cyberphysical Systems ◽  
Industrial Internet Of Things ◽  
Industrial Internet ◽  
Ontological Approach ◽  
Exchange Information ◽  
Upper Level ◽  
Main Components

Nowadays, the concept of the industrial Internet of things is considered by researchers as the basis of Industry 4.0. Its use is aimed at creating a single information space that allows to unite all the components of production, starting from the processed raw materials to the interaction with suppliers and users of completed goods. Such a union will allow to change the established business processes of production to increase the customization of end products for the consumer and to reduce the costs for its producers. Each of the components is described using a digital twin, showing their main characteristics, important for production. The heterogeneity of these characteristics for each of the production levels makes it very difficult to exchange information between them. To solve the problem of interaction between individual components this paper proposes to use the ontological approach to model the components of industrial socio-cyberphysical systems. The paper considers four scenarios of interaction in the industrial Internet of things, based on which the upper-level ontology is formed, which describes the main components of industrial socio-cyberphysical systems and the connections between them.

scholarly journals МЕТОД РАСШИРЕНИЯ МОДЕЛИ ЛОГИСТИЧЕСКОЙ ЦЕПИ ПОСТАВОК, ПРЕДСТАВЛЕННОЙ В ФОРМЕ ДВУХУРОВНЕВОЙ ВЛОЖЕННОЙ СЕТИ ПЕТРИ

2019 ◽  
pp. 82-90
Author(s):  
Игорь Владимирович Шостак ◽  
Yashar Rahimi
Keyword(s):  
Supply Chain ◽  
Network Model ◽  
Business Processes ◽  
Raw Materials ◽  
Network Models ◽  
Raw Material ◽  
Wide Range ◽  
Dried Fruit ◽  
Time Dependencies ◽  
High Level

The issues related to the development of adequate network models of the processes of creating, deploying and supporting the functioning of the full logistics supply chain of dried fruit (SCDF) in Ukraine are considered. It is shown that the creation and operation of the SCDF, compared to other SCM class systems, raises a number of specific problems caused by the complexity of the interaction of raw material suppliers (fresh fruit), manufacturers of final products (drying, packaging), storage terminals, distributors, 3PL and 4PL providers (retailers). These problems are due to the fact that the interaction of participants in business processes in the SCDF generates a lot of material, financial and information flows, as well as flows of services from sources of raw materials to the final consumer. The variety of world regions from which dried fruit is delivered to Ukraine, a wide range of products supplied, yield, currency fluctuations, seasonality are the causes of a high level of uncertainty in the processes of formation and decision-making by the SCDF participants. The urgency of the problem is substantiated, the essence of which is to develop a temporal component in the network model of the SCDF, which adequately reflects in time the logistic processes that take place during the operation of the supply chain. A model of a full SCDF in the form of a two-level nested Petri net (NPN) is considered. At the same time, the network model of SCDF functioning in the form of a NPN includes two types of objects - the central link reflecting the activity of the focusing company on processing raw materials (dried fruits), and a number of subnets that simulate the activity of suppliers of raw materials and distributors of finished products. It is indicated that to predict the consequences of the current (or some predetermined) situation and to respond to inquiries about the future state of elements of the SCDF, a predictive model can be used that explicitly takes into account time dependencies. In this case, requests can be about the time of occurrence of certain events, and the fact that certain circumstances are present at a certain point in time. A method is described for extending the network model of the SCDF to comply with the 'just-in-time' principle when modeling business processes that take place supply chain.

Design of Supplier Selection Procedure in Garment Company

2014 ◽  
Vol 606 ◽  
pp. 241-245
Author(s):  
Reni Amaranti ◽  
Agus N. Supena ◽  
Agelin S. Ramadhani
Keyword(s):  
Decision Making ◽  
Supplier Selection ◽  
Business Processes ◽  
Raw Materials ◽  
Selection Process ◽  
Selection Procedure ◽  
Purchasing Department ◽  
Quality Of Products ◽  
Hierarchy Process

The purchase of raw materials is very influential for the quality of products produced in addition to the process of making the product itself. Therefore, how to choose the supplier from the available alternatives is something that must be done properly in the process of procurement of raw materials especially for companies with many product variations and associated with many suppliers. This paper discusses about how to make supplier selection procedure for garment company with a case on a medium scale garment company in Bandung that manufactures veil and Moslem fashion. Mapping of business processes using IDEF0 was the first step in designing of supplier selection procedure. Then performed an analysis of the process which is usually done to identify the weaknesses and strengths of the process. The next step is create a design of supplier selection procedure that is more structured and measurable. In addition, also designed a tool that can be used in the supplier selection process, which is a simple application to determine the ranking of suppliers who will be selected based on the criteria specified. The application is based on the decision-making process with The Analytical Hierarchy Process approach that has been commonly used as a tool for decision-making with many alternative choices. In general, the resulting procedure would be beneficial for the company as a guide for those involved in the procurement process at the purchasing department, primarily for decision making in supplier selection.

Methodical Framework of the Support and Decision-making System for the Collection and Disposal of Organic Raw Materials

2015 ◽  
Vol 1 (1) ◽  
pp. 29-34
Author(s):  
Sergei Shvorov ◽  
◽  
Dmitry Komarchuk ◽  
Peter Ohrimenko ◽  
Dmitry Chyrchenko ◽  
...  
Keyword(s):  
Decision Making ◽  
Raw Materials ◽  
Decision Making System

STRATEGI MENINGKATKAN LOYALITAS KONSUMEN MAKANAN KHAS KOTA CURUP KABUPATEN REJANG LEBONG

2019 ◽  
Author(s):  
Onsardi Onsardi
Keyword(s):  
Swot Analysis ◽  
Raw Materials ◽  
External Factors ◽  
Consumer Loyalty ◽  
Internal Factors ◽  
The Public ◽  
Typical Food ◽  
Internal And External Factors

The title of this study is the Strategy of Increasing Consumer Food Loyalty in CurupCity, Rejang Lebong Regency (Case Study in "Henvian" Typical Food Industry). Thisresearch is based on the importance of strategies in increasing business and consumerloyalty to products sold.Strategies to increase business and consumer loyalty can bedone with a SWOT analysis. Place of this research is the "Henvian" shop that sellstypical Rejang lebong food. The method used in this study is descriptive qualitative.Informants in this study were people who were considered to know for certain about theHENVIAN Specialty Food Store in Curup City, Rejang Lebong Regency. The dataanalysis technique used in this study is a SWOT analysis to determine the strengths,weaknesses, opportunities and threats in a typical Rejang Lebong food business.By using SWOT analysis techniques that consist of strengths (weakness), weaknesses(weakness), opportunities (opportnity) and threats (threath). The results of this studycan be concluded that the internal factors that are the strength of the marketing strategyare the quality of the product that is good at a price affordable to the public andtourists, service that is friendly and responsive to consumer needs, as well astechnological advancements that facilitate the promotion of business. Internal factorsthat are a weakness are often lack of stock, there are some products that do not meet thestandard packaging, the product shelf life is short, employees do not use uniforms.External factors that become opportunities are a fairly high economic community,abundant raw materials while external factors that are a threat are the manycompetitors, an unstable economy, the price of basic needs increases. Based on theresults of the SWOT analysis of internal and external factors, the strategy used is toimprove product quality by improving the appearance of packaging and quality ofcontent and quality of service by providing uniforms to employees and providingstandards of service to consumers. .Keywords: Strategy, Consumer Loyalty, SWOT

Collaborative Action Research In Academic Administration

2019 ◽  
Vol 8 (3) ◽  
pp. 227-252
Author(s):  
Bradley C. Thompson
Keyword(s):  
Decision Making ◽  
Action Research ◽  
Collaborative Action Research ◽  
Team Members ◽  
Academic Administration ◽  
Leadership Culture ◽  
Collaborative Action ◽  
Working Together ◽  
Upper Level ◽  
Action Process

This research involved a study exploring the changes in an academic institution expressed through decision-making in a shifting leadership culture. Prior to the study, the school was heavily entrenched in authoritarian and centralized decision-making, but as upper-level administrators were exposed to the concept of collaborative action research, they began making decisions through a reflection and action process. Changing assumptions and attitudes were observed and recorded through interviews at the end of the research period. The research team engaged in sixteen weekly cycles of reflection and action based on an agenda they mutually agreed to and through an analysis of post-research interviews, weekly planning meetings, discussions, and reflection and action cycles. Findings revealed experiences centering around the issues of:  The nature of collaboration- it created discomfort, it created a sense of teamwork, it created difficulty.  The change of environment in the process- team members began to respect each other more, and the process became more enjoyable.  The freedom and change in the process- freedom to voice opinions and to actively listen, the use of experience to lead elsewhere in the school.  How issues of power are better understood by working together- the former process was less collaborative, politics will always be part of the process. As a result of this study, members have started using this decision-making methodology in other areas of administration.

scholarly journals Deep Learning-Based Differentiation between Mucinous Cystic Neoplasm and Serous Cystic Neoplasm in the Pancreas Using Endoscopic Ultrasonography

Diagnostics ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1052
Author(s):  
Leang Sim Nguon ◽  
Kangwon Seo ◽  
Jung-Hyun Lim ◽  
Tae-Jun Song ◽  
Sung-Hyun Cho ◽  
...  
Keyword(s):  
Decision Making ◽  
Deep Learning ◽  
Network Model ◽  
Endoscopic Ultrasonography ◽  
Data Augmentation ◽  
Clinical Information ◽  
Training Data ◽  
Fine Tuning ◽  
Cystic Neoplasm ◽  
Cystic Neoplasms

Mucinous cystic neoplasms (MCN) and serous cystic neoplasms (SCN) account for a large portion of solitary pancreatic cystic neoplasms (PCN). In this study we implemented a convolutional neural network (CNN) model using ResNet50 to differentiate between MCN and SCN. The training data were collected retrospectively from 59 MCN and 49 SCN patients from two different hospitals. Data augmentation was used to enhance the size and quality of training datasets. Fine-tuning training approaches were utilized by adopting the pre-trained model from transfer learning while training selected layers. Testing of the network was conducted by varying the endoscopic ultrasonography (EUS) image sizes and positions to evaluate the network performance for differentiation. The proposed network model achieved up to 82.75% accuracy and a 0.88 (95% CI: 0.817–0.930) area under curve (AUC) score. The performance of the implemented deep learning networks in decision-making using only EUS images is comparable to that of traditional manual decision-making using EUS images along with supporting clinical information. Gradient-weighted class activation mapping (Grad-CAM) confirmed that the network model learned the features from the cyst region accurately. This study proves the feasibility of diagnosing MCN and SCN using a deep learning network model. Further improvement using more datasets is needed.

Alignment and Identification of the Relationships between Key Performance Indicators in a Multilevel Tree Structure to Support Transportation Agency Decisions

2021 ◽  
pp. 036119812110190
Author(s):  
Hector Donaldo Mata ◽  
Mohammed Hadi ◽  
David Hale
Keyword(s):  
Machine Learning ◽  
Performance Indicators ◽  
Business Processes ◽  
Key Performance Indicators ◽  
Ordinary Least Squares ◽  
Learning Tools ◽  
Least Squares Regression ◽  
Upper Level ◽  
Selection Operator ◽  
Transportation Agencies

Transportation agencies utilize key performance indicators (KPIs) to measure the performance of their traffic networks and business processes. To make effective decisions based on these KPIs, there is a need to align the KPIs at the strategic, tactical, and operational decision levels and to set targets for these KPIs. However, there has been no known effort to develop methods to ensure this alignment producing a correlative model to explore the relationships to support the derivation of the KPI targets. Such development will lead to more realistic target setting and effective decisions based on these targets, ensuring that agency goals are met subject to the available resources. This paper presents a methodology in which the KPIs are represented in a tree-like structure that can be used to depict the association between metrics at the strategic, tactical, and operational levels. Utilizing a combination of business intelligence and machine learning tools, this paper demonstrates that it is possible not only to identify such relationships but also to quantify them. The proposed methodology compares the effectiveness and accuracy of multiple machine learning models including ordinary least squares regression (OLS), least absolute shrinkage and selection operator (LASSO), and ridge regression, for the identification and quantification of interlevel relationships. The output of the model allows the identification of which metrics have more influence on the upper-level KPI targets. The analysis can be performed at the system, facility, and segment levels, providing important insights on what investments are needed to improve system performance.

scholarly journals Integrating multiple fuzzy expert systems under restricting requirements 

2012 ◽  
Vol 52 (No. 4) ◽  
pp. 187-196
Author(s):  
S. Aly ◽  
I. Vrana
Keyword(s):  
Decision Making ◽  
Expert Systems ◽  
Business Processes ◽  
New Product ◽  
Decision Problems ◽  
Food Chains ◽  
Problem Context ◽  
Multiple Factors ◽  
Decision Consistency ◽  
Fuzzy Expert Systems

The multiple, different and specific expertises are often needed in making YES-or-NO (YES/NO) decisions for treating a variety of business, economic, and agricultural decision problems. This is due to the nature of such problems in which decisions are influenced by multiple factors, and accordingly multiple corresponding expertises are required. Fuzzy expert systems (FESs) are widely used to model expertise due to its capability to model real world values which are not always exact, but frequently vague, or uncertain. In addition, they are able to incorporate qualitative factors. The problem of integrating multiple fuzzy expert systems involves several independent and autonomous fuzzy expert systems arranged synergistically to suit a varying problem context. Every expert system participates in judging the problem based on a predefined match between problem context and the required specific expertises. In this research, multiple FESs are integrated through combining their crisp numerical outputs, which reflect the degree of bias to the Yes/No subjective answers. The reasons for independency can be related to maintainability, decision responsibility, analyzability, knowledge cohesion and modularity, context flexibility, sensitivity of aggregate knowledge, decision consistency, etc. This article presents simple algorithms to integrate multiple parallel FES under specific requirements: preserving the extreme crisp output values, providing for null or non-participating expertises, and considering decision-related expert systems, which are true requirements of a currently held project. The presented results provides a theoretical framework, which can bring advantage to decision making is many disciplines, as e.g. new product launching decision, food quality tracking, monitoring of suspicious deviation of the business processes from the standard performance, tax and customs declaration issues, control and logistic of food chains/networks, etc. 

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