Abdelaziz Bouras

Morphological analysis for product design

Analysis plays a significant role during product design. Thanks to computational tools; it contributes highly in product optimisation while decreasing design cost and time. For analysis applications, the adaptation of the product geometry is required and consists of producing an idealised model out of a product solid one. This paper presents a form of features based tool to aid the integration of analysis during the design process. It allows producing an analysis model out of a part solid model. This tool is based on a morphological analysis of the solid model followed by a two-phase process: simplification and idealisation. The tool provides an easy way to make computer-aided design model modifications implied by the analysis results; thanks to features parameterisation and a reconstruction process. Both allow us to create a solid model on the basis of the idealised one, by using parameterised reconstruction operators.

Supply chain management: a framework to characterize the collaborative strategies

The current intense competition forces enterprises to pay attention to supply chain collaboration with their upstream and downstream partners. Different collaborative strategies such as quick response (QR), efficient consumer response (ECR), vendor managed inventory (VMI) or collaborative planning, forecasting and replenishment (CPFR) have already been proposed. The key to ensuring that the supply chain partners are progressing on the right track of creating the best-in-class practice lays in their ability to choose the appropriate strategy. The current paper proposes a framework, based on analysis grids and graphical representations, which help to better characterize these strategies. The analysis grids use several characterization criteria to express the collaboration nature and its extent. For a better understanding, this framework is then applied to the CPFR strategy.

Collaboration and integration through information technologies in supply chains

Supply chain management encompasses various processes including various conventional logistics activities, and various other processes These processes are supported – to a certain limit – by coordination and integration mechanisms which are long-term strategies that give competitive advantage through overall supply chain efficiency. Information technology, by the way of collecting, sharing and gathering data, exchanging information, optimising process through package software, is becoming one of the key developments and success of these collaboration strategies. This paper proposes a study to identify the methods used for collaborative works in the supply chain and focuses on some of its areas, as between a company and its suppliers (i.e., inventory sharing) and its customers (i.e., customer demand, forecasting), and also the integration of product information in the value chain.

B2B relationship management: a framework to explore the impact of collaboration

This article aims to propose an integrated framework, based on two levels, able to characterise collaborative relation between two or more partners in a supply chain, evaluating their related performances. In the first level, related to the context point of view, the most common parameters, identified from a literature review, characterising a relationship between two partners, have been used to build an integrated analysis framework. The second level is related to the performance side and has been achieved through two main attributes: the perceived satisfaction of the relation and its perceived effectiveness. The implementation of the approach has been achieved through a survey of different companies, so as to propose a first analysis on how the characteristics of a relation impact its performance. A new dashboard is considered as an operative tool of the proposed approach, which allows to follow all the attributes which best characterise each relation type, as well as the sensitivity of the perceived performance for each attribute.

Integration between MES and Product Lifecycle Management

Today, within the global Product Lifecycle Management (PLM) approach, success of design, industrialization and production activities depends on the ability to improve interaction between information systems that handle such activities. Enterprises deploy mainly PLM system, Enterprise Resource Planning system (ERP) and Manufacturing Execution System (MES) in order to manage sufficient product-related information and provide better customer-products. This paper proposes a methodological approach to integrate product data generated during product design, industrialization and production. This involves the PLM and MES integration. Thus, the proposed approach aims to overcome the problem of data heterogeneity by proposing a mediation system resolving syntactic and semantic conflicts.

The use of process specification language for cutting processes

Today, manufacturers have to adapt their industrial systems, more frequently respecting tighter costs and delays. The main difficulty is that the people and the software tools designed to simulate the manufacturing planning use different vocabularies than the people or software applications that actually implement the process plan. This paper uses the Process Specification Language (PSL) as a neutral and rigorous base for modelling basic concepts of cutting processes. Primitives ontologies are identified and defined and will be the core of future PSL extensions for cutting processes. Finally, an example shows how ontologies are used within a particular context.

Detection and resolution of semantic inconsistency and redundancy in an automatic ontology merging system

In recent years, researchers have been developing algorithms for the automatic mapping and merging of ontologies to meet the demands of interoperability between heterogeneous and distributed information systems. But, still state-of-the-art ontology mapping and merging systems is semi-automatic that reduces the burden of manual creation and maintenance of mappings, and need human intervention for their validation. The contribution presented in this paper makes human intervention one step more down by automatically identifying semantic inconsistencies in the early stages of ontology merging. We are detecting semantic heterogeneities that occur due to conflicts among the set of Generalized Concept Inclusions, Property Subsumption Criteria, and Constraint Satisfaction Mechanism in local heterogeneous ontologies, which become obstacles for the generation of semantically consistent global merged ontology. We present several algorithms to detect such semantic inconsistencies based on subsumption analysis of concepts and properties in local ontologies from the list of initial mappings. We provide ontological patterns for resolving these inconsistencies automatically. This results global merged ontology free from ‘circulatory error in class/property hierarchy’, ‘common class between disjoint classes/properties’, ‘redundancy of subclass/subproperty of relations’ and other types of ‘semantic inconsistency’ errors. Experiments on the real ontologies show that our algorithms save time and cost of traversing local ontologies, improve system’s performance by producing only consistent accurate mappings, and reduce the users’ dependability for ensuring the satisfiability of merged ontology.

Disjoint-Knowledge Analysis and Preservation in Ontology Merging Process

Ontology mapping and merging systems play a vital role that aim at promoting automatic interoperability among different heterogeneous systems, agents, web services or groups in open environments such as Semantic Web. These systems help ontologists to resolve different types of conflicts among local ontologies to produce global merged ontology. This paper provides three contributions to the study and design of ontology merging systems that provides complete, consistent and coherent merged global ontology. First, we analyze that one of the important merge requirements is ignored yet by state-of-the-art ontology mapping and merging systems, i.e., Disjoint-knowledge Preservation between concepts. Second, we introduce another type of semantic conflict, which needs attention for consistent and coherent merged ontology, i.e., Alignment Conflict among disjoint relations. Third, we present an overview of our semantic-based ontology merger, DKP-OM, as a solution for the generation of global merged ontology that is consistent, coherent and complete with respect to local ontologies. We conclude that disjoint knowledge analysis for ontology merging is very much helpful for the detection of inconsistent initial mappings that originate from concept name or instance matching strategies, reduce search space for concept matching, and promote consistent computation by exploiting reliable logical inference on facts by axiomatization.

Towards ensuring Satisfiability of Merged Ontology

Abstract The last decade has seen researchers developing efficient algorithms for the mapping and merging of ontologies to meet the demands of interoperability between heterogeneous and distributed information systems. But, still state-of-the-art ontology mapping and merging systems is semi-automatic that reduces the burden of manual creation and maintenance of mappings, and need human intervention for their validation. The contribution presented in this paper makes human intervention one step more down by automatically identifying semantic inconsistencies in the early stages of ontology merging. Our methodology detects inconsistencies based on structural mismatches that occur due to conflicts among the set of Generalized Concept Inclusions, and Disjoint Relations due to the differences between disjoint partitions in the local heterogeneous ontologies. We present novel methodologies to detect and repair semantic inconsistencies from the list of initial mappings. This results in global merged ontology free from ‘circulatory error in class/property hierarchy’, „common class/instance between disjoint classes error’, ‘redundancy of subclass/subproperty relations’, ‘redundancy of disjoint relations’ and other types of „semantic inconsistency’ errors. In this way, our methodology saves time and cost of traversing local ontologies for the validation of mappings, improves performance by producing only consistent accurate mappings, and reduces the user dependability for ensuring the satisfiability and consistency of merged ontology. The experiments show that the newer approach with automatic inconsistency detection yields a significantly higher precision.

An Approach of Decision-Making Support Based on Collaborative Agents for Unexpected Rush Orders Management

Decisions at different levels of the supply chain can no longer be considered independently, since they may influence profitability throughout the supply chain. This paper focuses on the interest of multi-agent paradigm for the collaborative coordination in global distribution supply chain. Multi-agent computational environments are suitable for a broad class of coordination and negotiation issues involving multiple autonomous or semiautonomous problem solving contexts. An agent-based distributed architecture is proposed for better management of rush unexpected orders. This paper proposes a first architecture validated by a real and industrial case.