Gábor Erdös

Computing lower and upper bounds for a large-scale industrial job shop scheduling problem

In this paper we present a case study from the lighting industry concerned with the scheduling of a set of job families each representing the production of a particular end-item in a given quantity. It is a job shop type problem, where each job family has a number of routing alternatives, and the solution has to respect batching and machine availability constraints. All jobs of the same job family have a common release date and a common due date, and they differ only in size. The objective is to minimize the total tardiness of the job families, rather than that of individual jobs. We propose a two-phase method based on solving a mixed-integer linear program and then improving the initial solution by tabu search. We evaluate our method on real-world as well as generated instances.

Digital enterprise solution for integrated production planning and control

Digital enterprise technologies combined with sophisticated optimization algorithms can significantly contribute to the efficiency of production. The paper introduces a novel approach for integrated production planning and control, with the description of the mathematical models and solution algorithms. The deterministic optimization algorithms are complemented by a discrete-event simulation system to assess solution robustness in case of disturbances. The methods are illustrated by describing two prototype systems and by some experimental results obtained in an industry-initiated project.

STEP-NC Data Model Development for Wire-EDM Manufacturing

Abstract This paper presents a new data model for wire-EDM technology. It was developed for data exchange between CAD-CAM-CNC machines. This data model will become part of the ISO-14649(Data model for Computerized Numerical Controllers) international standard. The overall structure and the design goals of this new STEP based data model is presented.

Scheduling the Maintenance of Wind Farms for Minimizing Production Loss

With the extensive and worldwide increase of the market share of wind energy, the optimal operation of wind farms gains an ever growing signicance. The planning and scheduling of maintenance operations is both decisive for turbine availability and a key component of the operational costs. This paper introduces a formal model of wind farm maintenance, and proposes a mixed-integer programming formulation for the problem of optimizing detailed maintenance schedules. Initial results are presented and directions for future research are pointed out.

Parametric tool correction algorithm for 5-axis machining

Today, 5-axes CAM systems generate tool paths as a sequence of tool postures, which define the position of the tool tip and the orientation of the tool axis. This tool posture data file is usually called CLDATA, because it stores the position of the Cutter Location. In current practice, if the tool correction problem arises on the shop-floor, or at the machining simulation level, it can only be solved by sending back the code to the CAM system for re-generation. This iterative procedure is slow and very inefficient. In this article, a data model is specified that stores machine independent and dependent information separately. Based on this segmented data model a general method is presented to solve the tool correction problem for 5-axis milling machines. The new data model and the provided algorithms allow us to solve tool correction and possible other setup problems on the shop floor level. The algorithm is developed for ball-, flat- and radius-ended tools and is valid for 5-axis milling machine with open kinematic chain.