Ontology-Assisted Enterprise Information Systems Integration in Manufacturing Supply Chain

Ontology-Assisted Enterprise Information Systems Integration in Manufacturing Supply Chain

Kamalendu Pal (City, University of London, UK)
DOI: 10.4018/978-1-7998-1831-1.ch005

Abstract

Manufacturing communities around the globe are eagerly witnessing the recent developments in semantic web technology (SWT). This technology combines a set of new mechanisms with grounded knowledge representation techniques to address the needs of formal information modelling and reasoning for web-based services. This chapter provides a high-level summary of SWT to help better understand the impact that this technology will have on wider enterprise information architectures. In many cases it also reuses familiar concepts with a new twist. For example, “ontologies” for “data dictionaries” and “semantic models” for “data models.” This chapter presents the usefulness of a proposed architecture by applying a theory to integrating data from multiple heterogeneous sources which entails dealing with semantic mapping between source schema and a resource description framework (RDF) ontology described declaratively using specific query language (i.e. SPARQL) queries. Finally, the semantic of query rewriting is further discussed and a query rewriting algorithm is presented.
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Introduction

All manufacturing business today appreciates the value and consequence of building an effective supply chain as part of enterprise proliferation and profitability. There exist different types of the industry-specific supply chain (e.g. automotive, pharmaceutical, apparel, agriculture). In simple, the supply chain is a system with organization, people, technology, activity, information and resource involved in, to deliver a product or service from suppliers to customers. Supply chain activity transforms natural resources, raw materials and components into final products, and delivers them to customers. A network is composed of the enterprises and enterprise departments involved in this process. The most important requirements of supply chain operation are to minimize the inventory, create seamless material and information flow, effective communication must exist among the market, sale, purchase, manufacturing plan and control, appropriate customer delivery service, after-sales service, and so on. Therefore, a supply chain is a network of facilities and distribution options that performs the functions of material procurement, the transformation of these materials into intermediate and finished products, and distribution of these finished products to customers (Pal, 2017). Supply Chain Management (SCM) aims at improving the allocation, management and control of logistical resources. In this way, manufacturing SCM is a set of synchronized activities for integrating suppliers, manufacturers, transporters, and efficient customer service so that the right product or service is delivered at the right quantities, at the right time, to the right places. The ultimate objective of SCM is to achieve sustainable competitive advantage (Pal, 2019).

The first signs of SCM were perceptible in Toyota Motor Manufacturing’s Just-In-Time (JIT) procurement system. Particularly, JIT was used to control suppliers to the factory just in the right quantities, to the right location, and at the right time, in order to optimize system-wide costs and customer affordability. The main goal was to reduce inventory level drastically, and to regulate the suppliers’ interaction with the production line more effectively. It consisted of two distinct flows through the supply chain organizations: material and information. The scope of the supply chain begins with the source of supply and ends at the point of consumption. It extends much further than simply a concern with the physical movement of materials. Equal emphasis is given to supplier management, purchasing, inventory-management, manufacturing management, facilities planning, customer service, information flow, transport and physical distribution. Some of the important business processes, along supply chain, are shown in Figure 1.

The ultimate objective with the implementation of SCM, suppliers and customers are viewed as partners and their relationship becomes a cooperative one as enterprises in the supply chain recognize that coordination among partners within the supply chain is a key factor of success. In order to operate a supply chain efficiently in a cooperative manner, all related functions across the supply chain must operate in an integrated way the various partners within the supply chain must be efficient with respect to service provisions. This balances Constraint Satisfaction Problem (CSP) with appropriate customer service, minimum inventory holding cost and optimal unit cost. In this complex CSP environment, the design and operation of an effective supply chain is of fundamental importance for global manufacturing business.

It is worth noting that purchasing process does not finish when the customer places an order using an existing sales channel. Customer queries, before or after order placement, are inevitable. At the same time, the seller might want to contact customers with purchase confirmation and shipping information. Customer service encompasses all points of contact between the seller and the customer and is an important output of SCM. It results from the accumulated value of all business processes along the supply chain. These business processes are responsible for offering an acceptable level of customer service. Moreover, these business processes are also interdependent, if one business function fails to provide the expected level of customer service the chain is disrupted, and the scheduled workload in other areas is destabilized thereby jeopardizing customer satisfaction (Pal, 2018) (Pal, 2019).

Figure 1.

Diagrammatic representation of supply chain business process

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Key Terms in this Chapter

Linked Data: An approach taken to linking data such that it becomes more useful / accessible than it would be in isolation.

Supply Chain Management: A supply chain consists of a network of key business processes and facilities, involving end users and suppliers that provide products, services and information. In this chain management, improving the efficiency of the overall chain is an influential factor; and it needs at least four important strategic issues to be considered: supply chain network design, capacity planning, risk assessment and management, and performances monitoring and measurement. Moreover, the details break down of these issues need to consider in the level of individual business processes and sub-processes; and the combined performance of this chain. The coordination of these huge business processes and their performance improvement are the main objectives of a supply chain management system.

Structured Data: Data are stored in accordance with a strict schema for database management purpose.

XML: Extensible Markup Language (XML) is a simple, very flexible text format derived from SGML (Standard Generalized Markup Language). While XML was originally designed to meet the challenges of large-scale electronic publishing, it plays an increasingly significant role in the exchange of a wide variety of data on the web.

Ontology: Information sharing among supply chain business partners using information systems is an important enabler for supply chain management. There are diverse types of data to be shared across supply chain, namely – order, 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 conceptualization among hardware / software agents customers, and service providers) are known as explicit ontologies; and this help to exchange data and derived knowledge out of the data to achieve collaborative goals of business operations.

SPARQL Query: A SPARQL query usually contains a set of triple patterns, much like RDF triples, except that any of the subject, predicate and object may be a variable, whose bindings are to be found in the RDF data.

Resource Description Framework (RDF): The RDF is a standard for representing knowledge on the web. It is primarily designed for building the semantic web and has been widely adopted in database and datamining communities. RDF models a fact as a triple which consists of a subject (s), a predicate (p), and an object (o).

SPARQL: The SPARQL query language is a structured language for querying RDF data in a declarative fashion. Its core function is subgraph pattern matching, which corresponds to finding all graph homomorphism in the data graph for a query graph.

Relational Database: Relational database systems support processing of tuples of relations to generate a single result as a set of tuples. Relational algebra, relational calculus and structured query language (SQL) are used to specify queries on relational databases.

SQL: Structured Query Language (SQL) – a commonly-used language for querying relational database systems.

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