Artificial Intelligence in Supply Chain

SUPPLY CHAIN
ARTIFICIAL INTELLIGENCE IN SUPPLY CHAIN

The increased development and implementation of the technological innovations have
led to the drastic changes in the business processes. Among the various shifts, one major shift
can be seen in the logistics sector as well. The computer vision and language based artificial
intelligence (AI) have been changing the interaction of the logistics operators with the world.
The following work is aimed at evaluating the changing role of the artificial intelligence in
the supply chain and the efficiencies generated from the same.
The potential of Artificial Intelligence is quite vast in terms of the solution of complex
problems and searching information in the supply chain management area. The application of
AI in supply chain would be instrumental in terms of the elimination of the outdated
processes and updating of the same to be more streamlined, more successful, and more agile
(Gunasekaran, Dubey & Singh, 2016). The ways in which the artificial intelligence would be
instrumental for the supply chain process and the management has been elaborated as
follows.
It must be noted that the supply chain activities are recognized as having a waterfall
effect. Thus, the effect on one thing circulates to others in the form of a chain. The
implementation of the artificial intelligence would lead to steady flow of information and
enhance the areas such as inventory planning, location planning, consolidation of the frights,
and addressing the problems of scheduling (Lima-Junior & Carpinetti, 2017). The AI helps
the managers with improving the effectiveness of the inventory management by the reduction
of the inventory errors. The second field where the AI can yield effective results is the

transportation network design problems. The problems include the issues such as minimum
spanning tree problem, traffic assignment, vehicle routing problems, parking space
utilization, ramp metering in freeway networks and others. The AI based OR techniques are
more flexible, in terms of the conduct of the research and the simulation of the problems
(Plastino & Purdy, 2018). The yet another area that has been simplified is the purchasing and
the supply management. The make or buy decision are comprised of a number of issues such
as capital investment needed, the nature and intensity of the risk is involved, key strength of
the company, volume of goods expected to be produced and others. The complexity involved
in the said decisions calls for the set of systematic decision-aid tools, involving expert
systems. The artificial intelligence can enhance the automation of the on-line ordering
process, knowledge based systems to evaluate the on-line bids and the performance of the
bid-winning suppliers in the fulfilment of the orders (Tjahjono, Esplugues, Ares & Pelaez,
2017). Further, the artificial intelligence can be instrumental in searching the prospective
suppliers of the company through refinement of the processes like screening of the qualified
suppliers, evaluation of the suppliers in light of the multiple attributes, analysis of the online
catalogues, and the completion of the purchase order. The artificial intelligence can also aid
the organizations in the prevention of the specification ambiguity and thus substituting the
role of the human decision-maker (Vasant & DeMarco, 2015). . Thus, it can be stated that the
artificial intelligence can lead to the refinement of the strategic and tactical purchasing
decisions. One of the yet another important area that has been significantly affected by the