An agricultural products supply chain management to optimize resources and carbon emission considering variable production rate: Case of nonperishable corps

Mohammed Alkahtani; Muhammad Omair; Qazi Salman Khalid; Ghulam Hussain; Biswajit Sarkar

doi:10.3390/pr8111505

An agricultural products supply chain management to optimize resources and carbon emission considering variable production rate: Case of nonperishable corps

Mohammed Alkahtani, Muhammad Omair, Qazi Salman Khalid, Ghulam Hussain, Biswajit Sarkar

Department of Industrial Engineering

Research output: Contribution to journal › Article › peer-review

7 Citations (Scopus)

Abstract

The management of the man–machine interaction is essential to achieve a competitive advantage among production firms and is more highlighted in the processing of agricultural products. The agricultural industry is underdeveloped and requires a transformation in technology. Advances in processing agricultural products (agri-product) are essential to achieve a smart production rate with good quality and to control waste. This research deals with modelling of a controllable production rate by a combination of the workforce and machines to minimize the total cost of production. The optimization of the carbon emission variable and management of the imperfection in processing makes the model eco-efficient. The perishability factor in the model is ignored due to the selection of a single sugar processing firm in the supply chain with a single vendor for the pragmatic application of the proposed research. A non-linear production model is developed to provide an economic benefit to the firms in terms of the minimum total cost with variable cycle time, workforce, machines, and plant production rate. A numerical experiment is performed by utilizing the data set of the agri-processing firm. A derivative free approach, i.e., algebraic approach, is utilized to find the best solution. The sensitivity analysis is performed to support the managers for the development of agricultural product supply chain management (Agri-SCM).

Original language	English
Article number	1505
Pages (from-to)	1-26
Number of pages	26
Journal	Processes
Volume	8
Issue number	11
DOIs	https://doi.org/10.3390/pr8111505
Publication status	Published - 2020 Nov

Bibliographical note

Funding Information:
Funding: This work was supported by Researchers Supporting Project Number (RSP-2020/274), King Saud University, Riyadh, Saudi Arabia.

Funding Information:
This work was supported by Researchers Supporting Project Number (RSP-2020/274), King Saud University, Riyadh, Saudi Arabia. Acknowledgments: The work was supported by Researchers Supporting Project Number (RSP-2020/274), King Saud University, Riyadh, Saudi Arabia. The authors are also thankful to University of Engineering and Technology, Peshawar and GIK Institute for providing necessary technical assistance.

Publisher Copyright:
© 2020 by the authors. Licensee MDPI, Basel, Switzerland.

All Science Journal Classification (ASJC) codes

Bioengineering
Chemical Engineering (miscellaneous)
Process Chemistry and Technology

Access to Document

10.3390/pr8111505

Cite this

@article{6527ba66e2ea4339a35076c9e23d4b43,

title = "An agricultural products supply chain management to optimize resources and carbon emission considering variable production rate: Case of nonperishable corps",

abstract = "The management of the man–machine interaction is essential to achieve a competitive advantage among production firms and is more highlighted in the processing of agricultural products. The agricultural industry is underdeveloped and requires a transformation in technology. Advances in processing agricultural products (agri-product) are essential to achieve a smart production rate with good quality and to control waste. This research deals with modelling of a controllable production rate by a combination of the workforce and machines to minimize the total cost of production. The optimization of the carbon emission variable and management of the imperfection in processing makes the model eco-efficient. The perishability factor in the model is ignored due to the selection of a single sugar processing firm in the supply chain with a single vendor for the pragmatic application of the proposed research. A non-linear production model is developed to provide an economic benefit to the firms in terms of the minimum total cost with variable cycle time, workforce, machines, and plant production rate. A numerical experiment is performed by utilizing the data set of the agri-processing firm. A derivative free approach, i.e., algebraic approach, is utilized to find the best solution. The sensitivity analysis is performed to support the managers for the development of agricultural product supply chain management (Agri-SCM).",

author = "Mohammed Alkahtani and Muhammad Omair and Khalid, {Qazi Salman} and Ghulam Hussain and Biswajit Sarkar",

note = "Funding Information: Funding: This work was supported by Researchers Supporting Project Number (RSP-2020/274), King Saud University, Riyadh, Saudi Arabia. Funding Information: This work was supported by Researchers Supporting Project Number (RSP-2020/274), King Saud University, Riyadh, Saudi Arabia. Acknowledgments: The work was supported by Researchers Supporting Project Number (RSP-2020/274), King Saud University, Riyadh, Saudi Arabia. The authors are also thankful to University of Engineering and Technology, Peshawar and GIK Institute for providing necessary technical assistance. Publisher Copyright: {\textcopyright} 2020 by the authors. Licensee MDPI, Basel, Switzerland.",

year = "2020",

month = nov,

doi = "10.3390/pr8111505",

language = "English",

volume = "8",

pages = "1--26",

journal = "Processes",

issn = "2227-9717",

publisher = "MDPI AG",

number = "11",

}

TY - JOUR

T1 - An agricultural products supply chain management to optimize resources and carbon emission considering variable production rate

T2 - Case of nonperishable corps

AU - Alkahtani, Mohammed

AU - Omair, Muhammad

AU - Khalid, Qazi Salman

AU - Hussain, Ghulam

AU - Sarkar, Biswajit

N1 - Funding Information: Funding: This work was supported by Researchers Supporting Project Number (RSP-2020/274), King Saud University, Riyadh, Saudi Arabia. Funding Information: This work was supported by Researchers Supporting Project Number (RSP-2020/274), King Saud University, Riyadh, Saudi Arabia. Acknowledgments: The work was supported by Researchers Supporting Project Number (RSP-2020/274), King Saud University, Riyadh, Saudi Arabia. The authors are also thankful to University of Engineering and Technology, Peshawar and GIK Institute for providing necessary technical assistance. Publisher Copyright: © 2020 by the authors. Licensee MDPI, Basel, Switzerland.

PY - 2020/11

Y1 - 2020/11

N2 - The management of the man–machine interaction is essential to achieve a competitive advantage among production firms and is more highlighted in the processing of agricultural products. The agricultural industry is underdeveloped and requires a transformation in technology. Advances in processing agricultural products (agri-product) are essential to achieve a smart production rate with good quality and to control waste. This research deals with modelling of a controllable production rate by a combination of the workforce and machines to minimize the total cost of production. The optimization of the carbon emission variable and management of the imperfection in processing makes the model eco-efficient. The perishability factor in the model is ignored due to the selection of a single sugar processing firm in the supply chain with a single vendor for the pragmatic application of the proposed research. A non-linear production model is developed to provide an economic benefit to the firms in terms of the minimum total cost with variable cycle time, workforce, machines, and plant production rate. A numerical experiment is performed by utilizing the data set of the agri-processing firm. A derivative free approach, i.e., algebraic approach, is utilized to find the best solution. The sensitivity analysis is performed to support the managers for the development of agricultural product supply chain management (Agri-SCM).

AB - The management of the man–machine interaction is essential to achieve a competitive advantage among production firms and is more highlighted in the processing of agricultural products. The agricultural industry is underdeveloped and requires a transformation in technology. Advances in processing agricultural products (agri-product) are essential to achieve a smart production rate with good quality and to control waste. This research deals with modelling of a controllable production rate by a combination of the workforce and machines to minimize the total cost of production. The optimization of the carbon emission variable and management of the imperfection in processing makes the model eco-efficient. The perishability factor in the model is ignored due to the selection of a single sugar processing firm in the supply chain with a single vendor for the pragmatic application of the proposed research. A non-linear production model is developed to provide an economic benefit to the firms in terms of the minimum total cost with variable cycle time, workforce, machines, and plant production rate. A numerical experiment is performed by utilizing the data set of the agri-processing firm. A derivative free approach, i.e., algebraic approach, is utilized to find the best solution. The sensitivity analysis is performed to support the managers for the development of agricultural product supply chain management (Agri-SCM).

UR - http://www.scopus.com/inward/record.url?scp=85096291738&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85096291738&partnerID=8YFLogxK

U2 - 10.3390/pr8111505

DO - 10.3390/pr8111505

M3 - Article

AN - SCOPUS:85096291738

SN - 2227-9717

VL - 8

SP - 1

EP - 26

JO - Processes

JF - Processes

IS - 11

M1 - 1505

ER -

An agricultural products supply chain management to optimize resources and carbon emission considering variable production rate: Case of nonperishable corps

Abstract

Bibliographical note

All Science Journal Classification (ASJC) codes

Access to Document

Other files and links

Fingerprint

Cite this