Multihoist cyclic scheduling with fixed processing and transfer times

Cataloged from PDF version of article.In this paper, we study the no-wait multihoist cyclic scheduling problem, in which the processing times in the tanks and the transfer times between tanks are constant parameters, and develop a polynomial optimal solution to minimize the production cycle length.We first analyze the problem with a fixed cycle length and identify a group of hoist assignment constraints based on the positions of and the relationships among the part moves in the cycle.We show that the feasibility of the hoist scheduling problem with fixed cycle length is consistent with the feasibility of this group of constraints which can be solved efficiently. We then identify all of the special values of the cycle length at which the feasibility property of the problem may change. Finally, the whole problem is solved optimally by considering the fixed-cycle-length problems at these special values

Scheduling in flexible robotic manufacturing cells

Cataloged from PDF version of article.The focus of this thesis is the scheduling problems arising in robotic cells which consist of a number of machines and a material handling robot. The machines used in such systems for metal cutting industries are highly flexible CNC machines. Although flexibility is the key term that affects the performance of these systems, the current literature ignores this. As a consequence, the problems considered in the current literature are either too limiting or the provided solutions are suboptimal for the flexible systems. This thesis analyzes different robotic cell configurations with different sources of flexibility. This study is the first one to consider operation allocation problems and controllable processing times as well as some design problems and bicriteria models in the context of robotic cell scheduling. Also, a new class of robot move cycles is defined, which is overlooked in the existing literature. Optimal solutions are provided for solvable cases, whereas complexity analyses and efficient heuristic algorithms are provided for the remaining problems.Gültekin, HakanPh.D

An efficient optimal solution to the two-hoist no-wait cyclic scheduling problem

Hoist scheduling is a typical problem in the operation of electroplating systems. The cyclic scheduling policy is widely used in these systems in industry. Research on hoist scheduling has focused on the cyclic problem to minimize the cycle length. Most previous studies consider the single-hoist case. In practice, however, more than one hoist is often used in an electroplating line. This paper addresses the two-hoist, no-wait cyclic scheduling problem, in which the tank-processing times are constants and, upon completion of processing in a tank, the parts have to be moved to the next tank immediately. Based on the analysis of the problem properties, a polynomial algorithm is developed to obtain an optimal schedule. This algorithm first identifies a set of thresholds, which are special values of the cycle length, so that the feasibility property may change only at these thresholds. Feasibility checking is then carried out on each individual threshold in ascending order. The first feasible threshold found will be the optimal cycle length, and the corresponding feasible schedule is an optimal hoist schedule. © 2005 INFORMS

Novel approaches to cyclic job-shop problems with transportation

Scheduling problems can be found in almost any field of application in the real world. These problems may not only have different characteristics but they also imply more or less complex requirements. One specific class within this domain is the cyclic job-shop problem. It occurs in various areas reaching from industrial production planning down to the systems architecture of computers. With manufacturers in particular, one can find increasing demand for effective solution methods in order to tackle these scheduling problems efficiently. This thesis will deal with the Cyclic Job-Shop Problem with Blocking and Transportation. It arises in modern manufacturing companies, where the products move automatically between the different workstations, for instance. The problem itself is not new to the research community, but hardly any work has been done in solving it. Within this thesis we will try to close this gap and present some first approaches, discussing the structure of the problem and how it can be solved. As a result, we will provide three different solution methods, including an integer programming formulation, which is solved with a commercial solver, a branch and bound algorithm and a tabu search heuristic. All algorithms are tested on a range of data sets and compared with each other. Additionally, we have worked on a polynomial solvable subproblem, which has gained more interest in the literature. As a result, a new polynomial algorithm, that outperforms the existing ones in theory as well as in empirical tests (except for some special cases) is presented. This thesis concludes with a discussion about ideas of how to improve the presented methods and some other extensions to the investigated problem

New Solution Approaches for Scheduling Problems in Production and Logistics

The current cumulative PhD thesis consists of six papers published in/submitted to scientific journals. The focus of the thesis is to develop new solution approaches for scheduling problems encountering in manufacturing as well as in logistics. The thesis is divided into two parts: “ma-chine scheduling in production” and “scheduling problems in logistics” each of them consisting three papers. To have most comprehensive overview of the topic of machine scheduling, the first part of the thesis starts with two systematic review papers, which were conducted on tertiary level (i.e., re-viewing literature reviews). Both of these papers analyze a sample of around 130 literature re-views on machine scheduling problems. The first paper use a subjective quantitative approach to evaluate the sample, while the second papers uses content analysis which is an objective quanti-tative approach to extract meaningful information from massive data. Based on the analysis, main attributes of scheduling problems in production are identified and are classified into sever-al categories. Although the focus of both these papers are set to review scheduling problems in manufacturing, the results are not restricted to machine scheduling problem and the results can be extended to the second part of the thesis. General drawbacks of literature reviews are identi-fied and several suggestions for future researches are also provided in both papers. The third paper in the first part of the thesis presents the results of 105 new heuristic algorithms developed to minimize total flow time of a set of jobs in a flowshop manufacturing environ-ment. The computational experiments confirm that the best heuristic proposed in this paper im-proves the average error of best existing algorithm by around 25 percent. The first paper in second part is focused on minimizing number of electric tow-trains responsi-ble to deliver spare parts from warehouse to the production lines. Together with minimizing number of these electric vehicles the paper is also focused to maximize the work load balance among the drivers of the vehicles. For this problem, after analyzing the complexity of the prob-lem, an opening heuristic, a mixed integer linear programing (MILP) model and a taboo-search neighborhood search approach are proposed. Several managerial insights, such as the effect of battery capacity on the number of required vehicles, are also discussed. The second paper of the second part addresses the problem of preparing unit loaded devices (ULDs) at air cargos to be loaded latter on in planes. The objective of this problem is to mini-mize number of workers required in a way that all existing flight departure times are met and number of available places for building ULDs is not violated. For this problem, first, a MILP model is proposed and then it is boosted with a couple of heuristics which enabled the model to find near optimum solutions in a matter of 10 seconds. The paper also investigates the inherent tradeoff between labor and space utilization as well as the uncertainty about the volume of cargo to be processed. The last paper of the second part proposes an integrated model to improve both ergonomic and economic performance of manual order picking process by rotating pallets in the warehouse. For the problem under consideration in this paper, we first present and MILP model and then pro-pose a neighborhood search based on simulated annealing. The results of numerical experiment indicate that selectively rotating pallets may reduce both order picking time as well as the load on order picker, which leads to a quicker and less risky order picking process

Managing distributed flexible manufacturing systems

Per molti anni la ricerca scientifica si è concentrata sui diversi aspetti di gestione dei sistemi manifatturieri, dall’ottimizzazione dei singoli processi produttivi, fino alla gestione delle più complesse imprese virtuali. Tuttavia molti aspetti inerenti il coordinamento e il controllo, ancora presentano problematiche rilevanti in ambito industriale e temi di ricerca aperti. L’applicazione di tecnologie avanzate e di strumenti informatici evoluti non riesce da sola a garantire il successo nelle funzioni di controllo e di integrazione. Al fine di ottenere un alto grado di efficienza, è necessario supportare tali tecnologie e strumenti con dei modelli che siano in grado di rappresentare le funzionalità e i processi dei sistemi manifatturieri, e consentano di prevederne e gestirne l’evoluzione. Ne emerge l’esigenza di politiche di controllo e di gestio ne distribuite, che favoriscano l’auto-organizzazione e la cooperazione nei sistemi manifatturieri. I sistemi manifatturieri flessibili distribuiti (DFMS), in risposta a tale esigenza, sono sistemi di produzione dinamici in grado di garantire una risposta in tempo reale alla allocazione ottima delle risorse, e organizzare efficientemente le lavorazioni dei prodotti. In questa tesi viene proposta una modellizzazione a livelli per tali sistemi. Secondo tale rappresentazione un DFMS può essere visto come un grafo strutturato su più livelli, tale che: i vertici del grafo rappresentano le risorse interagenti nel sistema; ogni nodo di un livello rappresenta a sua volta un livello successivo. Partendo da questa rappresentazione, sono stati quindi sviluppati due modelli per lo studio dell’allocazione ottima delle risorse (task mapping) e per l’organizzazione di lavorazioni (task scheduling) che richiedono l’uso simultaneo di risorse condivise nel sistema. Il task mapping problem consiste nella suddivisione bilanciata di un certo insieme di lavorazioni tra le risorse del sistema. In questa tesi si è studiato il caso in cui le lavorazioni sono omogenee, non presentano vincoli di precedenza, ma necessitano di un certo volume di comunicazione tra le risorse cui sono assegnate per garantirne il coordinamento, incidendo in tal senso sulla complessità di gestione. L’analisi critica dei modelli che sono tipicamente usati in letteratura per rappresentare tale problema, ne hanno posto in evidenza l’inadeguatezza. Attraverso alcuni risultati teorici si è quindi dimostrato come il problema possa ricondursi ad un hypergraph partitioning problem. Studiando la formulazione matematica di tali problemi, e limitandosi al caso di due risorse produttive, si è infine giunti alla determinazione di una buona approssimazione sulla soluzione ottima. Il problema di sequenziamento delle lavorazioni (task scheduling) che richiedono l’uso simultaneo di risorse condivise è stato trattato nel caso specifico di celle robotizzate. E’ stata quindi dimostrata l’NP-completezza di questo problema ed è stata progettata una euristica di soluzione, validandone i risultati in diversi scenari produttivi.For several years, research has focused on several aspects of manufacturing, from the individual processes towards the management of virtual enterprises, but several aspects, like coordination and control, still have relevant problems in industry and remain challenging areas of research. The application of advanced technologies and informational tools by itself does not guarantee the success of control and integration applications. In order to get a high degree of integration and efficiency, it is necessary to match the technologies and tools with models that describe the existing knowledge and functionality in the system and allow the correct understanding of its behaviour. In a global and wide market competition, the manufacturing systems present requirements that lead to distributed, self-organised, co-operative and heterogeneous control applications. A Distributed Flexible Manufacturing System (DFMS) is a goal-driven and data-directed dynamic system which is designed to provide an effective operation sequence for the products to fulfil the production goals, to meet real-time requirements and to optimally allocate resources. In this work first a layered approach for modeling such production systems is proposed. According to that representation, a DFMS may be seen as multi-layer resource-graph such that: vertices on a layer represent interacting resources; a layer at level l is represented by a node in the layer at level (l-1). Then two models are developed concerning with two relevant managerial issues in DFMS, the task mapping problem and the task scheduling with multiple shared resources problem. The task mapping problem concerns with the balanced partition of a given set of jobs and the assignment of the parts to the resources of the manufacturing system. We study the case in which the jobs are quite homogeneous, do not have precedence constraints, but need some communications to be coordinated. So, jobs assignment to different parts causes a relevant communication effort between those parts, increasing the managerial complexity. We show that the standard models usually used to formal represent such a problem are wrong. Through some graph theoretical results we relate the problem to the well-known hypergraph partitioning problem and briefly survey the best techniques to solve the problem. A new formulation of the problem is then presented. Some considerations on an improved version of the formulation permit the computation of a good Lower Bound on the optimal solution in the case of the hypergraph bisection. The task scheduling with multiple shared resources problem is addressed for a robotic cell. We study the general problem of sequencing multiple jobs, where each job consists of multiple ordered tasks and tasks execution requires simultaneous usage of several resources. NP-completeness results are given. A heuristic with a guarantee approximation result is designed and evaluated