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.

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.

Innovation and information technology in management

2021 ◽  
pp. 68-72
Author(s):  
Muna Shehada ◽  
F.V. Akulinin
Keyword(s):  
Artificial Intelligence ◽  
Information Technology ◽  
Economic Development ◽  
Supply Chain ◽  
Business Processes ◽  
Resource Planning ◽  
Operating Costs ◽  
Financial Sustainability ◽  
Chain Management ◽  
Reducing Costs

Information technology, artificial intelligence and other innovative areas of economic development allow manufacturers to reduce their operating costs by improving resource planning. Optimizing supply chain management (SCM) can improve the efficiency of all business processes in an organization, while reducing costs and increasing financial sustainability.

Use of Information Technology in the Supply Chain Management of the Pharmaceutical Industry

2022 ◽  
pp. 137-168
Author(s):  
Saibal Kumar Saha ◽  
Sangita Saha ◽  
Ajeya Jha
Keyword(s):  
Artificial Intelligence ◽  
Information Technology ◽  
Cloud Computing ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Pharmaceutical Industry ◽  
Successful Implementation ◽  
Chain Management ◽  
Role Of Information

An efficient supply chain management helps to increase the productivity of a business. Use of information technology and concepts like artificial intelligence, blockchain, and cloud computing have integrated the different aspects of supply chain with its stakeholders. Published literature in the field of SCM, IT, and the pharmaceutical industry has been reviewed, and different aspects of innovation, technique, risks, advancements, factors, and models have been taken into consideration to form a comprehensive chapter focusing on the role of information technology in the supply chain management of the pharmaceutical industry. The chapter finds that IT has made a significant impact in improving the efficiency of SCM. But its successful implementation and collaboration with other firms is the key to success for an efficient SCM. Within each category, gaps have been identified.

Artificial Intelligence in Supply Chain Management

2020 ◽  
pp. 470-482
Author(s):  
Rana Özyurt Kaptanoğlu
Keyword(s):  
Artificial Intelligence ◽  
Supply Chain ◽  
Neural Nets ◽  
Business World ◽  
Chain Management ◽  
Artificial Intelligent ◽  
Artificial Neural Nets ◽  
Order Tracking ◽  
Chain Architecture ◽  
Storage Distribution

This chapter develops a method proposal regarding digitisation of variables in road, maritime, and airline transport, and makes parameters machinable, output-producing algorithms methods. Results regarding which artificial intelligence is proper to be used in storage, distribution, stock, and order tracking, supply chain architecture, and third- and fourth-party logistical practices are sought. For this, artificial neural nets, software techniques, artificial intelligent philosophy, and the reflections on the business world are analysed.

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