Involvement of controllable lead time and variable demand for a smart manufacturing system under a supply chain management

2021 ◽  
pp. 115464
Author(s):  
Bikash Koli Dey ◽  
Shaktipada Bhuniya ◽  
Biswajit Sarkar
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Lead Time ◽  
Manufacturing System ◽  
Smart Manufacturing ◽  
Variable Demand ◽  
Chain Management ◽  
Controllable Lead Time

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.

scholarly journals Coordination Supply Chain Management Under Flexible Manufacturing, Stochastic Leadtime Demand, and Mixture of Inventory

Mathematics ◽  
2020 ◽  
Vol 8 (6) ◽  
pp. 911 ◽  
Author(s):  
Asif Iqbal Malik ◽  
Biswajit Sarkar
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Lead Time ◽  
Cost Allocation ◽  
Nash Bargaining ◽  
Decision Variable ◽  
Theoretic Approach ◽  
Flexible Production ◽  
Allocation Model ◽  
Chain Management

The necessity of coordination among entities is essential for the success of any supply chain management (SCM). This paper focuses on coordination between two players and cost-sharing in an SCM that considers a vendor and a buyer. For random demand and complex product production, a flexible production system is recommended. The study aims to minimize the total SCM cost under stochastic conditions. In the flexible production systems, the production rate is introduced as the decision variable and the unit production cost is minimum at the obtained optimal value. The setup cost of flexible systems is higher and to control this, a discrete investment function is utilized. The exact information about the probability distribution of lead time demand is not available with known mean and variance. The issue of unknown distribution of lead time demand is solved by considering a distribution-free approach to find the amount of shortages. The game-theoretic approach is employed to obtain closed-form solutions. First, the model is solved under decentralized SCM based on the Stackelberg model, and then solved under centralized SCM. Bargaining is the central theme of any business nowadays among the players of an SCM to make their profit within a centralized and decentralized setup. For this, a cost allocation model for lead time crashing cost based on the Nash bargaining model with the satisfaction level of SCM members is proposed. The cost allocation model under Nash bargaining achieves exciting results in SCM coordination.

scholarly journals Analisis Kesesuaian Kegiatan Pergudangan dan Pemetaan Proses Pergudangan pada Salah Satu Warehouse Industri Farmasi di Jakarta

2020 ◽  
Vol 5 (3) ◽  
Author(s):  
Wahyu Ashri Aditya ◽  
Ida Musfiroh
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Lead Time ◽  
Chain Management

Manajemen rantai pasok (Supply Chain Management) pada aspek pergudangan di suatu Industri Farmasi merupakan parameter yang sangat penting dalam suatu rantai distribusi sediaan farmasi; yang terdiri atas penerimaan, penyimpanan hingga pengiriman produk farmasi. Sistem penyimpanan dan pengiriman obat di Industri Farmasi yang baik dan benar mengacu pada Cara Pembuatan Obat yang Baik (CPOB) Tahun 2018 Bab 6 tentang Cara Penyimpanan dan Pengiriman Obat yang Baik. Gudang yang belum menerapkan CPOB akan mengalami kerugian serta kerusakan fisik sediaan farmasi dan juga kerugian finansial akibat produk yang pasif di gudang. Hal ini berdampak kepada penurunan kualitas warehouse dari Industri tersebut. Selain itu, pemetaan proses gudang dilakukan guna melihat dan menghilangkan pemborosan dalam proses kerja agar lead time dapat diperpendek secara signifikan dan kualitas diciptakan dengan benar sejak awal. Maka dari itu, diperlukan adanya evaluasi kegiatan pergudangan dan pemetaan proses pergudangan pada warehouse salah satu Industri Farmasi di Jakarta yang bertujuan untuk melihat kesesuaian kegiatan Gudang dengan CPOB dan menghilangkan pemborosan pada gudang. Penelitian dilaksanakan selama bulan Maret 2020 dengan melakukan pengamatan secara observasional dan dilakukan evaluasi. Hasil pengamatan menunjukkan bahwa Industri Farmasi telah memenuhi ketentuan sesuai CPOB akan tetapi masih terdapat beberapa sistem yang memerlukan kesesuaian lebih lanjut dengan CPOB untuk menghindari waste (pemborosan) dalam proses kerja sehingga diperlukan CAPA untuk evaluasi pada Industri Farmasi tersebut.Kata Kunci: Evaluasi, Pergudangan, Warehouse, Industri Farmasi, CPOB, Waste.

scholarly journals Coordinating Supply-Chain Management under Stochastic Fuzzy Environment and Lead-Time Reduction

Mathematics ◽  
2019 ◽  
Vol 7 (5) ◽  
pp. 480 ◽  
Author(s):  
Asif Iqbal Malik ◽  
Biswajit Sarkar
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Lead Time ◽  
Optimal Solution ◽  
Chain Model ◽  
Setup Cost ◽  
Chain Management ◽  
The Impact ◽  
Collaborative Supply Chain Management

In this paper, a supply-chain (SC) coordination method based on the lead-time crashing is proposed for a seller–buyer system. By considering different transportation modes, we control the lead-time (LT) variability. For the first time, we have attempted to determine the impact of the reliable and unreliable seller in a continuous-review supply-chain model under the stochastic environment. The authors discussed two reliability cases for the seller. First, we consider the seller is unreliable and in the second case, the seller is reliable. In addition, the demand during the lead time is stochastic with the known mean and variance. The proposed approach tries to find an optimal solution that performs well without a specific probability distribution. Besides, a discrete investment is made to reduce the setup cost, which will indirectly help supply-chain members to increase the total profit of the system. In the proposed model, the seller motivates the buyer by reducing lead time to take part in coordinating decision-making for the system’s profit optimization. We derive the coordination conditions for both members, the seller and the buyer, under which they are convinced to take part in the cooperative decision-making plan. Therefore, lead-time crashing is the proposed incentive mechanism for collaborative supply-chain management. We use a fixed-charge step function to calculate the lead-time crashing cost for slow and fast shipping mode. We give two numerical examples to validate the proposed models and demonstrate the service-level enhancement under the collaborative supply-chain management in case of an unreliable seller. Concluding remarks and future extensions are discussed at the end.

scholarly journals Traceable and Intelligent Supply Chain based on Blockchain and Artificial Intelligence

2021 ◽  
Vol 2070 (1) ◽  
pp. 012158
Author(s):  
Sachin Karadgi ◽  
Vadiraj Kulkarni ◽  
Shridhar Doddamani
Keyword(s):  
Artificial Intelligence ◽  
Supply Chain ◽  
Manufacturing System ◽  
Smart Manufacturing ◽  
Process Data ◽  
Control Data ◽  
Chain Management ◽  
Manufacturing Enterprises ◽  
Development Lifecycle ◽  
Narrow Context

Abstract Smart manufacturing focuses on maximizing the capabilities to increase multiple objectives, like cost, delivery, and quality, in manufacturing enterprises. This requires implementing product development lifecycle, production system lifecycle, and business cycle for supply chain management. In short, a considerable amount of data is generated in a given manufacturing enterprise. Likewise, progress has been made to adopt blockchain in financial industries, but the adoption is slow in non-financial sectors. The article elaborates a methodology for the realization of a traceable and intelligent supply chain. First, the methodology elaborates on the realization of traceability of enterprise entities, which are an integral part of the supply chain. In this case, each participating stakeholder of the supply chain is required internally to realize a smart manufacturing system with an extension to write critical control data to the blockchain (i.e., a subset of process data). Artificial Intelligence (AI) is being adopted in most industries. A supply chain stakeholder has access to its data and can employ AI to derive new insights. The data available with the stakeholder provides a narrow context. With blockchain, all the stakeholders have access to the data from other stakeholders. Subsequently, the insights derived by a stakeholder will be more meaningful. This will assist in realizing an intelligent supply chain.

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