Juan M. Novas

A Collaborative Framework between a Scheduling System and a Holonic Manufacturing Execution System

This paper presents developments on a collaborative framework between a centralized manufacturing scheduling system (SS) and a decentralized manufacturing execution system (MES). The paper intends to integrate such systems with the aim of reducing the existing gap between detailed manufacturing scheduling systems and lower level systems, like MESs. Moreover, the framework exploits the benefits of each specialized technology and complements their capabilities in order to collaborate at runtime. The SS is based on constraint programming (CP) technology, while the holonic MES or HMES implements the PROSA reference architecture and applies the delegate multi-agent system pattern (D-MAS). The scheduling system generates a good quality schedule, which execution is performed by the HMES. In turn, the HMES requires services from the SS in order to update the schedule. The paper also shows the impact that disruptive events have on the execution performance. Experimental results have shown a trade-off between efficiency and stability metrics.

An Approach for the Integration of a Scheduling System and a Multi-Agent Manufacturing Execution System. Towards a Collaborative Framework.

Abstract The paper presents advances in the development of a collaborative framework between a centralized scheduling system (SS) and a decentralized manufacturing execution system (MES). The SS is based on constraint programming (CP) technology, while the MES implements the PROSA reference architecture and applies the delegate multi-agent system pattern (D-MAS). The CP scheduling system generates a good quality global schedule, which in turn is executed by the MES. The framework is intended to develop capabilities to collaborate at runtime, exploiting the benefits of each specialized technology. Moreover, this work aims to show the impact on the execution process performance when an unexpected disruptive event occurs and turns the on-going schedule - as it was originally provided by the SS - into an infeasible one. The experimental results have shown a trade-off between efficiency and stability measures.

A comprehensive CP approach for the scheduling of resource-constrained multiproduct multistage batch plants

Abstract This work presents a novel, efficient and expressive Constraint Programming (CP) approach to the short-term scheduling problem of multistage batch plants. The CP model accounts for many features found in industrial settings and allows modeling operational policies that group batches of the same product into campaigns. Product campaigns simplify the plant operation and allow reducing scrap and changeover times. The formulation has been extensively tested with various examples, including large-scale ones, and different objective functions. Comparisons with results reported in recent contributions are also presented and discussed.

A Reactive Scheduling Approach Based on Domain-Knowledge

Real world industrial environments frequently face unexpected events that generally disrupt in-progress production schedules. This contribution presents advances in the development of a support framework to address the repair-based reactive scheduling of industrial batch plants. When facing an unforeseen event, the framework is capable of capturing the current operational plan and its status. Based on this information, a rescheduling problem specification is developed. Tasks to be rescheduled are identified and, for them, the set of the most suitable rescheduling action types (e.g. shift, reassign, etc.) is specified. For a given specification, many solutions to the problem could exist. Then, the second step of this approach relies on the generation of a constraint programming (CP) model to address the rescheduling problem just specified. To create such model each rescheduling action type is automatically transformed into different constraints. In addition, a search strategy based on domain knowledge can also be developed. Finally, the solution of the CP model and its associated search strategy will render the repaired schedule in which the repair action types that were suggested will be instantiated. A case study of a multiproduct multistage batch plant is presented, where an event of unit failure is considered.

A Novel CP Approach for Scheduling an Automated Wet-Etch Station

Abstract This paper presents a novel, efficient, and expressive Constraint Programming (CP) model to address the Automated Wet-Etch Station (AWS) scheduling problem. This CP model overcomes some of the shortcomings of previous approaches since it can explicitly take into account the time employed by any empty robot to move itself from the bath where it dropped a wafer lot to another bath where it is required to pick up a different lot. Such transfer time, which depends on the travel distance, needs to be considered to avoid overexposure of wafers in chemical baths. The formulation has been extensively evaluated in productivity maximization scenarios