Antonio Grieco

Object-oriented modeling and simulation of flexible manufacturing systems: a rule-based procedure

Abstract Simulation by a software model, is one of the most frequently used techniques for the analysis and design of manufacturing systems. In the software engineering research area, the object-oriented approach has fully demonstrated to be an effective technique with respect to the design and implementation phases of complex software projects. Even if object-oriented programming has proven to be a powerful technique, a systematic design method should also be used in order to implement reliable software, in particular in the development of simulation models. This paper presents a new procedure to develop flexible manufacturing system (FMS) simulation models, based on the UML analysis/design tools and on the ARENA ® simulation language. The two main features of the proposed procedure are the definition of a systematic conceptual procedure to design FMS simulation models and of a set of rules for the conceptual model translation in a simulation language. The goal is to improve the software development efficiency through a rule-based approach and to add some of the fundamental object-oriented features to the ARENA ® simulation environment.

Rolling-horizon and fix-and-relax heuristics for the parallel machine lot-sizing and scheduling problem with sequence-dependent set-up costs

In this paper we develop new rolling-horizon and fix-and-relax heuristics for the identical parallel machine lot-sizing and scheduling problem with sequence-dependent set-up costs. Unlike previous papers, our procedures are based on a compact formulation relying on the hypotheses of identical machines. This feature makes our approach suitable for large-scale applications (with hundreds of machines) arising in the textile and fiberglass industries. Moreover, our procedures are shown to provide a feasible solution for any feasible instance. Comparisons with lower bounds provided by a truncated branch-and-bound show that the gap between the best heuristic solution and the lower bound never exceeds 3%.

A Review of Different Approaches to the FMS Loading Problem

Loading in flexible manufacturing systems (FMSs) is affected by the characteristics of the FMS under analysis, by the type of plant where the FMS is introduced, and by the production planning hierarchy where the loading module operates. We propose an analysis of the various aspects that influence the problem formulation, identifying the alternatives available in real systems and possible future evolutions. We then provide a survey of different approaches proposed in the literature to tackle the loading problem. Articles are classified according to the type of FMS analyzed, the objective function, and the constraints. Finally, based on our analysis, we suggest some problem issues which need to be addressed, and also directions for future research.

Robust scheduling of parallel machines with sequence-dependent set-up costs

In this paper we propose a robust approach for solving the scheduling problem of parallel machines with sequence-dependent set-up costs. In the literature, several mathematical models and solution methods have been proposed to solve such scheduling problems, but most of which are based on the strong assumption that input data are known in a deterministic way. In this paper, a fuzzy mathematical programming model is formulated by taking into account the uncertainty in processing times to provide the optimal solution as a trade-off between total set-up cost and robustness in demand satisfaction. The proposed approach requires the solution of a non-linear mixed integer programming (NLMIP), that can be formulated as an equivalent mixed integer linear programming (MILP) model. The resulting MILP model in real applications could be intractable due to its NP-hardness. Therefore, we propose a solution method technique, based on the solution of an approximated model, whose dimension is remarkably reduced with respect to the original counterpart. Numerical experiments conducted on the basis of data taken from a real application show that the average deviation of the reduced model solution over the optimum is less than 1.5%.

Simulation of tool and part flow in FMSs

We deal with the problem of tool management in FMSs that are provided with a tool carrier. The paper reports on a procedure to determine how many copies of the various types of tools should be present and describes a simulation study that investigates the possibility of reducing the investment in tools by sharing the tools among several machining centres. The performance of the FMS is measured by the fraction of time that machining centres are unable to work because the tool required for the next imminent operation is not present in the tool magazine of the machining centre. These waiting times depend on the selection of tools available at the central tool magazine and on the tool management policy. The paper shows that by a proper management of the tool transport system it is possible to obtain savings in tooling while preserving the performance of the FMS.

Fix and Relax Heuristic for a Stochastic Lot-Sizing Problem

This paper addresses a particular stochastic lot-sizing and scheduling problem. The evolution of the uncertain parameters is modelled by means of a scenario tree and the resulting model is a multistage stochastic mixed-integer program. We develop a heuristic approach that exploits the specific structure of the problem. The computational experiments carried out on a large set of instances have shown that the approach provides good quality solutions in a reasonable amount of time.

Parallel tabu search for a pickup and delivery problem under track contention

This article introduces the Pickup and Delivery Problem under Track Contention, a particular vehicle routing problem in which loads have to be transported between origin-destination pairs by means of vehicles travelling along a capacitated network. Two sequential heuristics and a parallel tabu search are proposed. Computational experiments show that the parallel tabu search is able to find much better solutions than the sequential procedures, although this comes at the expense of a higher computing time.

A new algorithm to rank temporal fuzzy sets in fuzzy discrete event simulation

In this paper fuzzy set theory was applied to discrete event simulation to model uncertainty in input data. Various approaches to fuzzy simulation have been proposed in the literature, even if many of the problems are still to be solved. The key points are how to manage the simulation event list and how to update the fuzzy simulation clock. These two tasks are mainly based on the ranking algorithm. In the following, the classical algorithms were applied to rank temporal fuzzy sets and the results obtained were compared with the ones obtained by the proposed ranking algorithm. The comparison was performed by analyzing a simple case study in the manufacturing field. The results show how the new ranking algorithm can be very useful in a fuzzy simulation environment.

An online approach to dynamic rescheduling for production planning applications

Manufacturing firms must often consider how to plan the production of a new order while containing the impact on the existing plan. Two approaches are typically used to solve the problem: online scheduling and rescheduling. State-of-the-art for both strategies is analyzed and methods available in the literature are proved to be inefficient for real world cases coming from production planning problems in a manufacturing firm. We propose an alternative approach combining the most effective aspects of both traditional approaches. The already available production plan and the characteristics of the new order to be planned are studied and used in order to generate a new production plan that meets two requirements: containing the number of changes to the existing plan and minimizing the delays due to the newly planned order. Constraint programming is used to implement the proposed approach. Results on case studies are also provided to evaluate the effectiveness of the proposed approach.

Using simulated annealing to design a material-handling system

Among all material-handling systems used in modern factories, those based on automated guided vehicles have, for many reasons, met with great success. AGV systems are much more flexible than traditional systems such as fixed-path conveyors, allowing dynamic reconfiguration of guidepaths in accordance with factorys changing transportation needs.