concept of semantic information pool for manufacturing supply networks

Concept of Semantic Information Pool for manufacturing supply networks

mr. Milan Zdravković1, Prof. dr Hervé Panetto2, Prof. dr Miroslav Trajanović1

1Faculty of Mechanical Engineering, University of Niš, Innovation Center for Information Technologies2Research Centre for Automatic Control (CRAN – UMR 7039), Nancy-Université, CNRS

Fifth International Working Conference ''Total Quality Management – Advanced and Intelligent Approaches'', June 1st – 4th, 2009, Belgrade, Serbia

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Objectives

General objectives Facilitate networking of individual SME’s Manage complexity of individual SME’s involvement in multiple

supply chains Specific objective

Design and develop SW system for provision of support in decision making processes, related to…

Partner selection Configuration (organizational change)

Production planning Capacity management Risk management

Process management Knowledge management Exception handling..

…of manufacturing supply networks


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Traditional supply chains vs. Virtual enterprises 1/2

Traditional supply chains Relation-oriented Relations are dyadic – rarely expanded to include vendors’

vendors or customers’ customers Supplier Relationship Management

80% is human effort and 20% information technology There is a tendency to reduce number of suppliers because of

possible relation cost reductions Motivation examples

Complexity of supply relationship is high and volume of buy is high (Wendy)

Potential for cost reduction is high and potential for innovation is high (Colgate-Palmolive)

High frequency of transactions between parties Degree of asset specificity


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Traditional supply chains vs. Virtual enterprises 2/2

Virtual Enterprises “Temporary networks of independent companies who come

together quickly to exploit fast-changing opportunities” (Brown and Zhang, 1999)

Customer-oriented Motivation examples

One-of-a-kind production or service task After sales services for a product line

Derived from inter-organizational networks Cooperative Goals

Eliminate all non-value activities, including the costs of controlling each other’s operations

Improve responsiveness Achieve adaptive behavior Improve product

In a survey in USA (2002), it is found that 35% of innovation in the product comes from the supply chain. In Toyota, its 60%.


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Benefits of traditional supply chains

FOCUS (time-to-market -> market share) After 11/9, Zara launched whole new line of black

clothes in only 14 days Japan retail chain 7/11 schedule deliveries to each

store within a ten-minute margin. Less than 6 hours after catastrophic earthquake in Kobe,

1995, they delivered rice balls to stores with 125 motorcycles and 7 helicopters


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Problem statements

High-speed, low-cost supply chains are unable to respond to unexpected structural changes in (customized) demand or supply

Uncertainty of long-term supply chains centrally managed by a focal partner When cutting costs is strictly imposed by a focal partner, it can

have very negative effect throughout supply chain High level of integration reduces flexibility of small and

medium enterprises Investments in technical framework for enterprise

integration, which could maximize the efficiency and productivity of virtual enterprise, cannot be justified in a short term


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Proposed solution features

Formalized collaboration model Transparent, loose, dominantly asynchronous, externally

coordinated integration, based on

semantic interoperability where models may be classified with regards to the needed maturity

level of interoperation and the way networked enterprises applications have to cooperate

Parameterized and quantified representation of enterprise’s abilities to perform, with the goal to

reduce the scope and volume of associative thinking in the associated decision making processes


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Conceptual model of SIP4SUPProcess Definition

Process Generation EngineAggregated Competence

Association featuresProduction Competence

Production Competence

Production Competence

Goal DefinitionCapability Definition

Acquisition Services

Storage EngineMatchmaking

Engine

Ontology of production competences

Reference ontologies

Reference process models

Decomposition

MetadaAvailability

DataAffiliation Data

Mapping

Mapping


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Managed information

Asset Data and Metadata. General information on partners’ competences (location,

ownership, product, resources, knowledge, historical performance etc.) availability, ontologies, registered services for pulling availability information and their service contracts;

Competence availability data. Accurate Available-To-Promise (ATP) stock for all products;

Accurate schedule and scale for planned machining and human resources utilization;

Networking affiliation data. Various aspects of networking and affiliation. For example, stock

and resources availability data accessibility (synchronous or asynchronous communication), IPR issues, privacy issues, terms and conditions for affiliation, import and export permits, etc;


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Formalization approach

Inter-organizationalNetwork Ontology

EnterpriseOntology

ProductOntology

CompetenceOntology

EnterpriseOntology

TOVEOntologyREA

OntologyeUML

Ontology

ProcessOntology

SCOROntology

CPFROntology

WSMOOntology

VOSTER

ECOLEADOntology

VOMAP

Enable automatic characterization of instances by inference

Axiomatic representation of concepts Use taxonomies for

achieving semantic precision


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Inter-organizational Network Ontology

Actor

------

Network

------

CooperationNetwork

------

CoordinationNetwork

------

CollaborationNetwork

Group

IndividualOrganization

------

SupplierAsset

Product

Information

Process

Activity

Goal

------

InformationSupplier

------

ProductSupplier

hasMember

isExecutedBy

hasInput

hasOutput

supply

Product:Product

REA:Agent = Enterprise:EOEntity=

FOAF:Agent

CoordinationService

WSMO:webService

Competence

Competence:Competence

derivedFrom

ProcessTemplate

hasTemplate

SCOR:ProcessDefinition=CPFR:ProcessDefinition

hasCompetence

------

Restructuration

OrganizationalChange

AtomicActivityhasActivity

------

AggregatedCompetence

AtomicCompetence

hasAtomicCompetence


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Competences ontology Competence is quantitatively

described ability of a partner to perform in certain area of business


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Integrated product ontology

Assembly ≡ ((hasPart.Part)∩(isPartOf.Part))

Product ≡ ((hasUNSPSCCode.String)∩Part)

ContextualPart ≡ ((hasContext.Context) ∩ Part)

FunctionalPart ≡ (ContextualPart ∩ ((hasEffect.ContextualPart) U (isAffectedBy.ContextualPart)))

Industrial categorization schemes UNSPSC ontology

implemented by SKOS

Design and functional product representation Improved

inferrence


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Referenced formal models Enterprise

REA: Resources-Events-Agents. Based on framework for transaction processing of economic phenomena in a shared

data environment Enterprise Ontology

Collection of terms and definitions relevant to business enterprises TOVE Ontology

Set of integrated (foundational and business) ontologies for the modelling of both commercial and public enterprises

Enterprise UML Service

WSMO: Web Services Modeling Ontology Collaborative organizations

VOSTER (Virtual Organizations Cluster) Consolidation of relevant concepts, types, features and indicators of virtual

organizations VOMAP

Roadmap design for collaborative virtual organizations in dynamic business ecosystems ECOLEAD

Characterization of Collaborative Networked Organizations Process

SCOR: Supply Chain Operations Reference-model Cross-industry standard diagnostic tool for supply chain management

CPFR: Collaborative Planning, Forecasting and Replenishment Concept that aims to enhance supply chain integration by supporting and assisting joint

practices


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Conclusion

Proposed approach is not intended to replace traditional supply chain management concepts It tends to provide solution to new market

circumstances and expand field of opportunities for SME’s

Expected benefits For focal partners

Single point of view to 360o of supply chain For small and medium enterprises

Knowledge management New industry sector

Business brokerage


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Conclusion: Expected effect to Virtual Enterprises Lifecycle

Formation Operation and evolution Dissolution

Selection

Restructuring

Planning Execution

Risk management

Exception handling

Knowledge management

Process templatesProcess

templates IntegrationCoordinationIntegration

Coordination

Integrated view to overall capability

of a network

Integrated view to overall capability

of a network

MetamorphosisFormalization of organizational

change and impact

Formalization of organizational

change and impactProcess

compensation templates

Process compensation

templates

Ontology learning

Assertion of inferred axioms

Ontology learning

Assertion of inferred axioms

Thank you for your attention

Contact:

http://icit.masfak.ni.ac.yuMilan Zdravković, [email protected]

Innovation Center for Information Technology - ICIT, Faculty of Mechanical Engineering, University of Niš

concept of semantic information pool for manufacturing supply networks

Technology

lowcost supply chains

availability information

general information

product line

information technologies

information technology

managed information

enterprise integration