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| Content Provider | Springer Nature Link |
|---|---|
| Author | Zayati, Ahlem Biennier, Frédérique Moalla, Mohamed Badr, Youakim |
| Copyright Year | 2010 |
| Abstract | The Lean Manufacturing approach requires advanced and efficient manufacturing technologies in order to meet customer demands. Manufacturing companies have increased their productivity and efficiency over time by implementing new strategies, business processes and IT solutions. Best practices also allow companies to achieve on-demand manufacturing through the integration of pull flow production strategy. In order to achieve agility to meet business needs, a key for success is a flexible integration of different information system components to enable the flow of exchanged data and information. To insure the agility of an enterprise’s organization, ISA S-95 standard can be used to determine which information has to be exchanged between system components. We propose an Industrial System Integration Architecture, a Lean Enterprise Service Bus which relies on Lean Manufacturing constraints based on semantic aspects with respect to the ISA S-95 standard. This architecture aims at enhancing the interoperability between the production system and the global enterprise information system in terms of business and manufacturing requirements and establishes semantic interoperability to achieve an industrial semantic. |
| Starting Page | 125 |
| Ending Page | 139 |
| Page Count | 15 |
| File Format | |
| ISSN | 09565515 |
| Journal | Journal of Intelligent Manufacturing |
| Volume Number | 23 |
| Issue Number | 1 |
| e-ISSN | 15728145 |
| Language | English |
| Publisher | Springer US |
| Publisher Date | 2010-04-20 |
| Publisher Place | Boston |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Pull strategy Lean manufacturing Industrial service Enterprise service bus Service-oriented architecture Manufacturing execution system Control, Robotics, Mechatronics Production/Logistics/Supply Chain Manufacturing, Machines, Tools |
| Content Type | Text |
| Resource Type | Article |
| Subject | Industrial and Manufacturing Engineering Artificial Intelligence Software |
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