scholarly journals An Agricultural Products Supply Chain Management to Optimize Resources and Carbon Emission Considering Variable Production Rate: Case of Nonperishable Corps

Processes ◽  
2020 ◽  
Vol 8 (11) ◽  
pp. 1505
Author(s):  
Mohammed Alkahtani ◽  
Muhammad Omair ◽  
Qazi Salman Khalid ◽  
Ghulam Hussain ◽  
Biswajit Sarkar
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Production Rate ◽  
Carbon Emission ◽  
Agricultural Products ◽  
Plant Production ◽  
Production Model ◽  
Data Set ◽  
Chain Management ◽  
Total Cost

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).

scholarly journals A COVID-19 Supply Chain Management Strategy Based on Variable Production under Uncertain Environment Conditions

2021 ◽  
Vol 18 (4) ◽  
pp. 1662
Author(s):  
Mohammed Alkahtani ◽  
Muhammad Omair ◽  
Qazi Salman Khalid ◽  
Ghulam Hussain ◽  
Imran Ahmad ◽  
...  
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Production Rate ◽  
Manufacturing System ◽  
Working Environment ◽  
Data Set ◽  
Manufacturing Firm ◽  
Chain Management ◽  
Ripple Effects ◽  
Multi Stage

The management of a controllable production in the manufacturing system is essential to achieve viable advantages, particularly during emergency conditions. Disasters, either man-made or natural, affect production and supply chains negatively with perilous effects. On the other hand, flexibility and resilience to manage the perpetuated risks in a manufacturing system are vital for achieving a controllable production rate. Still, these performances are strongly dependent on the multi-criteria decision making in the working environment with the policies launched during the crisis. Undoubtedly, health stability in a society generates ripple effects in the supply chain due to high demand fluctuation, likewise due to the Coronavirus disease-2019 (COVID-19) pandemic. Incorporation of dependent demand factors to manage the risk from uncertainty during this pandemic has been a challenge to achieve a viable profit for the supply chain partners. A non-linear supply chain management model is developed with a controllable production rate to provide an economic benefit to the manufacturing firm in terms of the optimized total cost of production and to deal with the different situations under variable demand. The costs in the model are set as fuzzy to cope up with the uncertain conditions created by lasting pandemic. A numerical experiment is performed by utilizing the data set of the multi-stage manufacturing firm. The optimal results provide support for the industrial managers based on the proactive plan by the optimal utilization of the resources and controllable production rate to cope with the emergencies in a pandemic.

Pengukuran Kinerja Supply Chain Menggunakan Supply Chain Operation Reference (Scor®) (Studi Kasus Koperasi Baitul Qiradh Baburrayyan)

2019 ◽  
Vol 2 (2) ◽  
Author(s):  
Raysa Aleyzia ◽  
Hasan Yudie Sastra
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Six Sigma ◽  
Green Beans ◽  
Chain Management ◽  
Total Cost ◽  
Target Value ◽  
Chain Operation ◽  
Cost To Serve ◽  
Supply Chain Operation

Manajemen supply chain yang tidak maksimal akan mempengaruhi kinerja suatu perusahaan. Di Aceh Tengah terdapat suatu koperasi yaitu Koperasi Baitul Qiradh (KBQ) Baburrayyan yang sudah menerapkan manajemen supply chain. Koperasi ini bergerak di bisnis perdagangan biji kopi (green bean). Penelitian ini bertujuan untuk mengukur kinerja supply chain dari KBQ Baburrayyan. Metode yang digunakan adalah SCOR® dengan praktik perbaikan Convergence of SCOR® with Lean and Six Sigma. Target kinerja yang diperoleh untuk total cost to serve adalah sebesar 94,71% dari nilai target 65,00% dan untuk return on supply chain fixed asset adalah sebesar 1,60 dari nilai target 2,50. Hasil yang diperoleh dari penggunaan praktik tersebut adalah terdapat 8 akar penyebab waste di antaranya kurangnya tenaga pengawas, training/briefing belum maksimal, kurangnya kepedulian tentang pentingnya K3, layout yang kurang efisien, belum adanya unit penyuluhan, alat yang masih sederhana, pekerjaan yang monoton, dan tidak dilarang secara tegas.   Supply chain management that is not optimal will affect the performance of a company. In Central Aceh there is a cooperative namely Koperasi Baitul Qiradh (KBQ) Baburrayyan which has implemented supply chain management. This cooperative is engaged in the business of trading in green beans. This study aims to measure the supply chain performance of KBQ Baburrayyan. The method used is SCOR® with the practice of improving Convergence of SCOR® with Lean and Six Sigma. The performance target for total cost to serve is 94.71% of the target value of 65.00% and the return on supply chain fixed assets is 1.60 of the target value of 2.50. The results obtained from the use of the practice are that there are 8 root causes of waste including lack of supervisors, training / briefing is not maximal, lack of concern about the importance of K3, inefficient layouts, absence of extension units, simple tools, monotonous work, and not strictly prohibited.

scholarly journals Controlling Waste and Carbon Emission for a Sustainable Closed-Loop Supply Chain Management under a Cap-and-Trade Strategy

Mathematics ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 466 ◽  
Author(s):  
Mowmita Mishra ◽  
Soumya Kanti Hota ◽  
Santanu Kumar Ghosh ◽  
Biswajit Sarkar
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
End Of Life ◽  
Carbon Emission ◽  
Closed Loop ◽  
Emission Trading ◽  
Third Party ◽  
Closed Loop Supply Chain ◽  
Chain Management ◽  
Carbon Emission Trading

Considering the increasing number of end-of-life goods in the context of improving the ambience and health of a population and their destructive impacts, recycling strategies are important for industries and organizations. In this article, a closed-loop supply chain management containing a single manufacturer, a single retailer, and a third party is introduced in which the manufacturer first propagates newly finished goods and then dispatches some of the finished goods to the retailer considering a single-setup multi-delivery policy. Due to shipping, carbon emission is taken into account as well as a carbon emission trading mechanism to curb the amount of carbon emissions by the retailer. For recycling through collection, inspection, remanufacturing, and landfill, the third party collects the end-of-life goods from its customers and ships perfect products to the manufacturer after a two-stage inspection. In this model, major sources of emissions such as shipping, replenishment orders, and inventory have been taken care of. The minimizing of the total cost relating to the container capacity, shipment numbers, and replenishment cycle length is the main objective of the closed-loop supply chain management for making the system more profitable. Expository numerical explorations, analysis, and graphic representations are conferred to elucidate this model, and it is observed that this model saves some percentage of the cost compared to the existing literature.

scholarly journals Big Data Driven Agricultural Products Supply Chain Management: A Trustworthy Scheduling Optimization Approach

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 49990-50002 ◽  
Author(s):  
Qian Tao ◽  
Chunqin Gu ◽  
Zhenyu Wang ◽  
Joseph Rocchio ◽  
Weiwen Hu ◽  
...  
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Agricultural Products ◽  
Data Driven ◽  
Optimization Approach ◽  
Scheduling Optimization ◽  
Chain Management

Carbon Emission Assessment for Typical Household Appliances Orienting the Green Supply Chain Management for Enterprises

2015 ◽  
Vol 1092-1093 ◽  
pp. 1591-1596
Author(s):  
Jian Hua Chen ◽  
Hui Ting Guo ◽  
Liang Sun ◽  
Wei Bo ◽  
Liang Chen
Keyword(s):  
Energy Efficiency ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Carbon Emission ◽  
Green Supply Chain Management ◽  
Green Supply Chain ◽  
Air Conditioner ◽  
Washing Machine ◽  
Chain Management ◽  
Efficiency Increase

This paper explores on the green supply chain management for enterprises based on the carbon emission assessment for products. The assessment showed that the priorities of green supply chain management measures were different for washing machine, air conditioner and microwave. The washing machine manufacturer should firstly focus on the measures to the upstream suppliers associated with the product eco-design, and secondly the product energy efficiency increase. The air conditioner manufacturer should first focus on the product energy efficiency increase, and secondly the eco-design, especially the refrigerant improvement. But the energy efficiency increase would be the only effective way for microwave. This work shows the method applies to the household appliance manufacturer to identify the green supply chain hot point, as the information of products is easier to obtain, and the effort performance could be shown intuitively along with the consuming process.

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