Supply Chain Resilience Management Using a Semantically-Enhanced Web Service Portal

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Introduction

Today's business appreciates the value of building an effective supply chain as part of corporate proliferation and profitability (Pal, 2018). There exist diverse industry-specific supply chains (e.g., automobile, pharmaceutical, agriculture, apparel). In a simplistic sense, the supply chain is a system with organization, people, technology, activity, information, and resource to deliver a product or service from suppliers to customers. In this way, supply chain activity transforms natural resources, raw materials, and components into final products and delivers them to customers. Hence, a supply chain is a network of facilities (e.g., procurement, transportation, manufacturing, warehouse facility, distribution center, and retail outlets), as shown in Figure 1. For example, procurement of raw materials from suppliers (e.g., node A) and manufacturing of products occurs at one or more manufacturing plants (e.g., node D). Ultimately, the transportation of finished products (e.g., node C) to intermediate storage (e.g., warehouse (e.g., node E)), distribution center (e.g., F)) for packaging and shipping to retailers (e.g., node G) or customers. The nodes' symbolic label (i.e., A, B, C, D, E) is related to Figure 1. Finally, the path from supplier to a customer can include several intermediaries, such as warehouses, distribution centers, wholesalers, and retailers, depending on the products and markets in which a supply chain operates.

The recent decades have been notable for significant changes in supply chains due to an increasing level of outsourcing business processes, globalization and a higher rate of support by technological innovation. The growing role of global supply chains was associated with increased interconnectedness among suppliers and manufacturers, which led to higher dependency among businesses in the supply chains and a higher level of supply chain complexity. This, in turn, resulted in efficient supply chains during stable business environments, but they are highly vulnerable to risks and disruptions.

Supply chains have faced challenges such as high demand variability, short life of products, and different expectations and requirements of customers; adapting to these challenges increased supply chain complexity and resulted in more instability and unpredictability. For example, manufacturers worldwide have recently faced rapid change across supply chains due to the coronavirus pandemic. It includes a change in market behaviour, diversified manufacturing, eco-friendly footprints, operational restructuring from mergers and acquisitions (M&A), pressure on pricing strategy, the rising cost of living, and fathomless customer expectations. Besides, the coronavirus pandemic has placed enormous strain on supply chain business processes and caused disturbances which adversely impact supply chain operations.

Figure 1.

Diagrammatic representation of supply chain business processes

These disturbances can have especially hidden characteristics that make them challenging to anticipate, and they can have severe adverse knock-on effects, not only in the supply chain business processes where they directly happen but also in the supply chains where the entities have an operational interface since they generally lead to a cascade effect. Also, disturbances may cause disruptions in information, materials, and financial flow between the business partners are only a few examples. These disruptions may negatively influence a supply chain's regular operational functions, consequently making it vulnerable and reducing its effective performance and competitive power. In other words, a disturbance is a consequential situation prominently counterproductive for the usual course of actions of the affected supply chain entities (Zsidisin, 2000). Typically, this situation implies taking appropriate decisions/actions to mitigate such effects. This way, it is essential to make a supply chain resilient to disturbances.

Key Terms in this Chapter

Ontology: Information sharing among supply chain business partners using information system is an important enabler for supply chain management. There are different types of data to be shared across the supply chain, namely – order, demand, inventory, shipment, and customer service. Consequently, information about these issues needs to be shared in order to achieve efficiency and effectiveness in supply chain management. In this way, information-sharing activities require that human and/or machine agents agree on common and explicit business-related concepts (the shared conceptualizations among hardware/software agents, customers, and service providers) are known as explicit ontologies; and these help to exchange data and derived knowledge out of the data to achieve collaborative goals of business operations.

Rule-Based Reasoning: In conventional rule-based reasoning, both common sense knowledge and domain specific domain expertise are represented in the forms of plausible rules (e.g., IF < precondition (s)> THEN < conclusion (s)>). For example, an instance of a particular rule: IF {( Sam has a driving license ) AND ( Sam is drunk ) AND ( Sam is driving a logistic distribution track ) AND ( Sam is stopped by police )} THEN {( Sam’s driving license will be revoked by the transport authority )}. Moreover, rule-based reasoning requires an exact match on the precondition(s) to predict the conclusion(s). This is very restrictive, as real-world situations are often fuzzy and do not match exactly with rule preconditions. Thus, there are some extensions to the basic approach that can accommodate partial degrees of matching in rule preconditions.

Description Logic: Knowledge-based software system relies on its stored knowledge and decision-making mechanisms. At the time of knowledge-based system design and development stages, software engineers use different knowledge representation techniques; and one of the techniques is symbolic logic-based representation. Different symbolic logic representation is used for knowledge presentation purpose. Description Logics (DLs) are a family of knowledge representation languages that can be used to represent the knowledge of an application domain in a structured way.

Semantic Web service: The advantages of integrating and coordinating supply chain business partners' information service applications, which are loosely distributed among participants with a wide range of hardware and software capabilities, are immensely important issue from the operation of global supply chain. Web service is an information technology-based solution for system interoperability; and in this technology business services are described in a standard web service description language (WSDL). Establishing the compatibility of services is an important prerequisite to service provision in web service operation. Web service has embraced the concepts of enriching distributed information systems with machine-understandable semantic metadata (known as ontology), and these new breed of web services are known as semantic web service. In this way, semantic web service provides a common framework for web-based services, which allows data to be shared and reused across application, enterprise, and extended community boundaries.

Case-Based Reasoning: Case-based reasoning (CBR) is one of the useful mechanisms for both modeling human reasoning and building intelligent software application systems. The basic principle of case-based reasoning systems is that of solving problems by adapting the solution of similar problems solved in the past. A CBR system consists of a case base , which is the set of all cases that are known to the system. The case base can be thought of as a specific kind of knowledge base that contains only cases. When a new case is presented to the system, it checks the case base for similar cases that are most relevant to the case in hand, in a selection process . If a similar case is found, then the system retrieves that particular case and attempts to modify it (if necessary) to produce a potential solution for the new case. The process is known as adaption .