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Intelligent Logistics and Production Sytstems
 
This research line is focused on the development of technologies based on Artificial Intelligence and Operations Research, for solving industrial optimization problems such as Production Planning & Scheduling, Computer Aided Process Planning (CAPP) and Collaborative Optimization.
 
     
Computer-Aided Process Planning (CAPP)
 
As time goes by, products grow in complexity, wich makes it difficult to design optimal manufacturing process plans. Computer Aided Process Planning (CAPP) aims at generating products process plans automatically, starting from a formal representation of the design.
 
Most of the CAPP systems proposed so far have limitations
which make it difficult their implementation or reduce their effectiveness: on the one hand there are knowledge base systems which do not support optimization; on the other hand there are systems specific to an industry or to a type of a product which make the system difficult to adapt to other cases. Besides, generative CAPP systems do not allow manufacture engineers to participate on the decision making process during the process planning.
 
This project aims at developing a CAPP system based on intelligent agents, which can be adapted to different industries and manufacturing resources, and allows manufacturing engineers to participate interactively through a mixed initiative interaction schema with the intelligent agent.
   
Generation of Scheduling Engines
 
Production Scheduling is an important function in the logistics management of the company as well as in the supply chain management. APS (Advanced Planning and Scheduling) systems are in charge of this function. If the scheduling process is complex and the APS systems available in the market do not satisfy the needs, then it is necessary to build it.
   
The APS core is the scheduling engine. Although many techniques to solve scheduling problems exist, little is known about methodologies to develop scheduling engines, this is the great gap between the academy and the industry. Normally a scheduling engine is developed from scratch, which requires too much time and money. Other approaches use frameworks with specialized components, which are very difficult to learn and they do not assure to reduce significantly the development times.
   
This project proposes to build an automatic generator of scheduling engines for specific domains. The final product is a scheduling engine, totally operative and adapted to the customer’s needs, obtained in the same time that takes to model an instance of domain. The modeling language must be adjusted to the terminology of the specific domain and to be flexible to model both usual and variable features of the domain.
   
Scheduling technology for industrial domains
 
Production Scheduling within industry is a demanding activity which requires much computing power to be carried out. Many R&D projects have been carried out in the past by researchers of the CEAL, by means of which much knowledge and expertise has been accumulated.

As a result, several technology transference projects in the production scheduling domain have been carried out, such as the PAP (Advanced Production Planning) system for the flexible packaging industry.
   
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©2008 CEAL - Centro de Estudios y Aplicaciones Logísticas
Facultad de Ingeniería - Universidad Nacional de Cuyo
Centro Universitario - Mendoza - Argentina