An analytical model for analyzing the value of information flow in the production chain model using regression algorithms and neural networks
Managing information flow has always been a challenging and critical driver of performance increase in manufacturing companies. Each bit of information related to the manufacturing process has an information flow value that can impact the process. Recent studies have focused on the traditional class...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2023-06-01
|
| Series: | Supply Chain Analytics |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2949863523000122 |
| _version_ | 1797237744034906112 |
|---|---|
| author | Florent Biyeme André Marie Mbakop Anne Marie Chana Joseph Voufo Jean Raymond Lucien Meva'a |
| author_facet | Florent Biyeme André Marie Mbakop Anne Marie Chana Joseph Voufo Jean Raymond Lucien Meva'a |
| author_sort | Florent Biyeme |
| collection | DOAJ |
| description | Managing information flow has always been a challenging and critical driver of performance increase in manufacturing companies. Each bit of information related to the manufacturing process has an information flow value that can impact the process. Recent studies have focused on the traditional classification algorithms methods to analyze the value of information flow. In this research paper, we use regression algorithms to develop an analytics model for the value of information flow in manufacturing shop floors of developing countries. The analysis shows that the Artificial Neural Network (ANN) has the best regression coefficient score of 0.775 with a prediction error of 0.0125. The lowest regression coefficient score of 0.323 was for the Multi-Linear Regression (MLR) with a prediction error of 0.0556. These results help companies use regression algorithms effectively to analyze the value of information flows on the manufacturing chains. |
| first_indexed | 2024-04-24T17:24:36Z |
| format | Article |
| id | doaj.art-2cd95d5d1f6b410a88273f9e292fdba8 |
| institution | Directory Open Access Journal |
| issn | 2949-8635 |
| language | English |
| last_indexed | 2024-04-24T17:24:36Z |
| publishDate | 2023-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Supply Chain Analytics |
| spelling | doaj.art-2cd95d5d1f6b410a88273f9e292fdba82024-03-28T06:41:23ZengElsevierSupply Chain Analytics2949-86352023-06-012100013An analytical model for analyzing the value of information flow in the production chain model using regression algorithms and neural networksFlorent Biyeme0André Marie Mbakop1Anne Marie Chana2Joseph Voufo3Jean Raymond Lucien Meva'a4National Advanced School of Engineering of Yaoundé (NASEY), Cameroon; Laboratory of Civil and Mechanical Engineering, Yaoundé, Cameroon; Department of Industrial and Mechanical Engineering, Yaoundé, CameroonNational Advanced School of Engineering of Yaoundé (NASEY), Cameroon; Laboratory of Civil and Mechanical Engineering, Yaoundé, Cameroon; Department of Industrial and Mechanical Engineering, Yaoundé, Cameroon; Corresponding author.National Advanced School of Engineering of Yaoundé (NASEY), Cameroon; Laboratory of Mathematics Informatics Bio-informatics and Applications, Yaoundé, Cameroon; Department of Computer Science Engineering, Yaoundé, CameroonNational Advanced School of Engineering of Yaoundé (NASEY), Cameroon; Laboratory of Civil and Mechanical Engineering, Yaoundé, Cameroon; Department of Industrial and Mechanical Engineering, Yaoundé, CameroonNational Advanced School of Engineering of Yaoundé (NASEY), Cameroon; Laboratory of Civil and Mechanical Engineering, Yaoundé, Cameroon; Department of Industrial and Mechanical Engineering, Yaoundé, CameroonManaging information flow has always been a challenging and critical driver of performance increase in manufacturing companies. Each bit of information related to the manufacturing process has an information flow value that can impact the process. Recent studies have focused on the traditional classification algorithms methods to analyze the value of information flow. In this research paper, we use regression algorithms to develop an analytics model for the value of information flow in manufacturing shop floors of developing countries. The analysis shows that the Artificial Neural Network (ANN) has the best regression coefficient score of 0.775 with a prediction error of 0.0125. The lowest regression coefficient score of 0.323 was for the Multi-Linear Regression (MLR) with a prediction error of 0.0556. These results help companies use regression algorithms effectively to analyze the value of information flows on the manufacturing chains.http://www.sciencedirect.com/science/article/pii/S2949863523000122Artificial neural networkInformation flow managementRegression algorithmsValue of informationProduction chain model |
| spellingShingle | Florent Biyeme André Marie Mbakop Anne Marie Chana Joseph Voufo Jean Raymond Lucien Meva'a An analytical model for analyzing the value of information flow in the production chain model using regression algorithms and neural networks Supply Chain Analytics Artificial neural network Information flow management Regression algorithms Value of information Production chain model |
| title | An analytical model for analyzing the value of information flow in the production chain model using regression algorithms and neural networks |
| title_full | An analytical model for analyzing the value of information flow in the production chain model using regression algorithms and neural networks |
| title_fullStr | An analytical model for analyzing the value of information flow in the production chain model using regression algorithms and neural networks |
| title_full_unstemmed | An analytical model for analyzing the value of information flow in the production chain model using regression algorithms and neural networks |
| title_short | An analytical model for analyzing the value of information flow in the production chain model using regression algorithms and neural networks |
| title_sort | analytical model for analyzing the value of information flow in the production chain model using regression algorithms and neural networks |
| topic | Artificial neural network Information flow management Regression algorithms Value of information Production chain model |
| url | http://www.sciencedirect.com/science/article/pii/S2949863523000122 |
| work_keys_str_mv | AT florentbiyeme ananalyticalmodelforanalyzingthevalueofinformationflowintheproductionchainmodelusingregressionalgorithmsandneuralnetworks AT andremariembakop ananalyticalmodelforanalyzingthevalueofinformationflowintheproductionchainmodelusingregressionalgorithmsandneuralnetworks AT annemariechana ananalyticalmodelforanalyzingthevalueofinformationflowintheproductionchainmodelusingregressionalgorithmsandneuralnetworks AT josephvoufo ananalyticalmodelforanalyzingthevalueofinformationflowintheproductionchainmodelusingregressionalgorithmsandneuralnetworks AT jeanraymondlucienmevaa ananalyticalmodelforanalyzingthevalueofinformationflowintheproductionchainmodelusingregressionalgorithmsandneuralnetworks AT florentbiyeme analyticalmodelforanalyzingthevalueofinformationflowintheproductionchainmodelusingregressionalgorithmsandneuralnetworks AT andremariembakop analyticalmodelforanalyzingthevalueofinformationflowintheproductionchainmodelusingregressionalgorithmsandneuralnetworks AT annemariechana analyticalmodelforanalyzingthevalueofinformationflowintheproductionchainmodelusingregressionalgorithmsandneuralnetworks AT josephvoufo analyticalmodelforanalyzingthevalueofinformationflowintheproductionchainmodelusingregressionalgorithmsandneuralnetworks AT jeanraymondlucienmevaa analyticalmodelforanalyzingthevalueofinformationflowintheproductionchainmodelusingregressionalgorithmsandneuralnetworks |