Decision-making in the manufacturing environment using a value-risk graph

A value-risk based decision-making tool is proposed for performance assessment of manufacturing scenarios. For this purpose, values (i.e. qualitative objective statements) and concerns (i.e. qualitative risk statements) of stakeholders in any given manufacturing scenario are first identified and are made explicit via objective and risk modeling. Next, performance and risk measures are derived from the corresponding objective and risk models to evaluate the scenario under study. After that, upper and lower bounds, and target value is defined for each measure in order to determine goals and constraints for the given scenario. Because of the multidimensionality nature of performance, the identified objectives and risks, and so, their corresponding measures are usually numerous and heterogeneous in nature. These measures are therefore consolidated to obtain a global performance indicator of value and global indicator of risk while keeping in views the inter-criteria influences. Finally, the global indicators are employed to develop minimum acceptable value and maximum acceptable risk for the scenario under study and plotted on the VR-Graph to demarcate zones of “highly desirable”, “feasible”, “and risky” as well as the “unacceptable” one. The global scores of the indicators: (value-risk) pair of the actual scenario is then plotted on the defined VR-Graph to facilitate decision-making by rendering the scenarios’ performance more visible and clearer. The proposed decision-making tool is illustrated with an example from manufacturing setup in the process context but it can be extended to product or systems evaluation

NEW HEURISTICS FOR MINIMISING TOTAL COMPLETION TIME AND THE NUMBER OF TARDY JOBS CRITERIA ON A SINGLE MACHINE WITH RELEASE TIME

<p>ENGLISH ABSTRACT: This paper considers the bi-criteria scheduling problem of simultaneously minimising the total completion time and the number of tardy jobs with release dates on a single machine. Since the problem had been classified as NP-Hard, two heuristics (HR9 and HR10) were proposed for solving this problem. Performance evaluations of the proposed heuristics and selected solution methods (HR7 and BB) from the literature were carried out on 1,100 randomly generated problems ranging from 3 to 500 jobs. Experiment results show that HR7 outperformed HR10 when the number of jobs (n) is less than 30, while HR10 outperformed HR7 for n≥ 30.</p><p>AFRIKAANSE OPSOMMING: In hierdie artikel word die bi-kriteria-skeduleringsprobleem bestudeer waar die totale voltooiingstyd en die aantal take wat laat is op ‘n enkele masjien geminimiseer moet word. Verskeie heuristieke word voorgestel en getoets om sodoende die beste benadering te identifiseer.</p&gt

Mathematical Modelling and Optimization of Flexible Job Shops Scheduling Problem

The flexible job shop scheduling problem (F-JSSP) is mathematically formulated. One novel position-based and three sequence-based mixed integer linear programming models are developed. Since F-JSSPs are strongly NP-hard, MILPs fail to solve large-size instances within a reasonable timeframe. Thus, a meta-heuristic, a hybrid of artificial immune and simulated annealing (AISA), is developed for use with larger instances of the F-JSSP. To prove the efficiency of developed MILPs and AISA, they are compared against state-of-the-art MILPs and meta-heuristics in literature. Comparative evaluations are conducted to test the quality and performance of the developed models and solution technique respectively. To this end, size complexities of the developed MILPs are investigated. The acquired results demonstrate that the proposed MILPs outperform the state-of-the-art MILP models in literature. Likewise, the proposed AISA outperforms all the previously developed meta-heuristics. The developed AISA has successfully been applied to a realistic case study from mould and die industry

Cost based rescheduling approach to handle disruptions in flexible manufacturing systems

Rescheduling is an essential operating task to efficiently tackle uncertainties and unexpected events frequently encountered in today's complex and flexible manufacturing systems. The main purpose of this thesis is to develop a real time reactive scheduling methodology in order to respond to such disturbances and uncertainties in a cost efficient manner. In order to assess the impact of schedule changes, a compound rescheduling cost function is developed based on machine, job, and material related rescheduling activities. A Total Rescheduling (TR) approach based on the Filtered-Beam-Search-heuristic algorithm (FBS) is proposed to generate a prespecified number of cost efficient suboptimal schedules by using the proposed cost function in case of each disruption. Thereafter, the current schedule is replaced by the alternative schedule which causes the minimum rescheduling cost. Responding to each single disruption with TR may cause system nervousness and increase the operational cost. Hence, a partial rescheduling approach is developed by a Modified Filtered-Beam-Search-heuristic algorithm (MFBSR) in order to generate a prespecified number of sub optimal cost-efficient schedules with a lower rescheduling cost and fewer deviations than TR. In order to validate the performance of the proposed methodologies, TR and MFBSR, different case studies and experimental designs have been performed considering various disruption scenarios. The performance of the suggested methods in terms of rescheduling cost, makespan efficiency and stability have been compared with similar rescheduling and repair methods in the literature. The results reveal that the proposed methodologies could be considered as competitive methods in responding to disruptions in flexible manufacturing system

Resolución del problema de flujo general flexible con fechas comprometidas y costes dependientes del intervalo de realización de las operaciones

En el marco de la problemática de la programación de operaciones en taller, en esta tesis se introduce un nuevo problema, que se identifica como problema de flujo general flexible (fJSP) con fechas comprometidas y costes dependientes del intervalo de realización de las operaciones. En el fJSP se deben tratar dos subproblemas, el de asignación de las operaciones a las máquinas que pueden ejecutarlas y el de secuenciación de las operaciones en cada una de las máquinas. Para este problema se propone, como función objetivo, minimizar la suma de los costes asociados a los adelantos y retrasos que se generan con respecto a la fecha de entrega comprometida y unos costes dependientes del intervalo de realización de las operaciones. De entre estos últimos se utiliza el coste de la energía necesaria para ejecutar las operaciones de los jobs (tareas) en las máquinas. Para resolver el problema propuesto se plantea un procedimiento dividido en tres pasos. En el Paso 1 se obtiene una secuencia inicial de jobs; en el Paso 2 se genera una solución inicial mediante un procedimiento que se basa principalmente en realizar, simultáneamente, la construcción y búsqueda del camino mínimo en un grafo polietápico para cada job; y en el Paso 3 se emplean procedimientos de mejora de la solución inicial. También se exponen los resultados de la experiencia computacional que evalúa el procedimiento de resolución propuesto. En los resultados se observa que el procedimiento favorece la programación de las operaciones respetando las fechas de entrega, y ayuda a reducir la factura de la empresa eléctrica, ya que en las soluciones de un conjunto de tipos de ejemplares se observa cómo se asignan, mayoritariamente, operaciones a máquinas con menor consumo de energía, y principalmente en aquellos intervalos de tiempo en los que el coste de la energía es menor. Al analizar los resultados de la experiencia computacional se observa, además, que el procedimiento encuentra la solución de ejemplares de diferente dimensión en un tiempo de proceso de ordenador razonableIn the context of the job-shop scheduling problem, this thesis introduces a new problem, which is identified as the flexible job-shop scheduling problem (fJSP) with due dates and energy costs that are dependent on the time interval in which the operations are processed. The fJSP involves two subproblems: that of assigning operations to the machines that can process them and that of sequencing the operations on each of the machines. For this problem, we propose an objective function that minimizes the sum of the costs of earliness and tardiness with respect to the due date and the costs that depend on the time interval in which the operations are processed. Regarding these costs, we have focused primarily on the cost of the energy required to process the jobs on the machines. To solve the proposed problem, we suggest a solution procedure that is divided into three steps. Step 1 involves obtaining an initial sequence of jobs, Step 2 involves generating an initial solution using a procedure based primarily on simultaneously constructing and finding the shortest path in a multistage graph for each job, and Step 3 involves implementing procedures for improving the initial solution. We report the results of the computational experiment used to test the proposed solution procedure. We were able to conclude from the results that the procedure is useful for scheduling operations while respecting due dates and that it could help reduce electricity bills, since the solutions to a set of example types demonstrated that operations were generally assigned to machines with a lower energy consumption, and mainly in time intervals in which the energy costs is low. When analysing the results of the computational experiment, we also observed that the procedure found the solution for examples of varying sizes in a fairly reasonable computer processing time

Metodología multiobjetivo basada en un comportamiento evolutivo para programar sistemas de producción flexible job shop. Aplicaciones en la industria metalmecánica

El objeto de estudio de la presente tesis es el taller de trabajo flexible en el sector metalmecánico. El problema de investigación se derivó a partir de la búsqueda sistemática de metodologías y algoritmos para programar sistemas productivos; se identificaron configuraciones de variables de proceso no abordadas en la literatura, lo que se considera un vacío en el conocimiento. Consecuente con lo anterior, se diseñó una metodología basada en un algoritmo evolutivo para programar los pedidos en un taller de trabajo flexible, con restricciones de tiempo, secuencia, mantenimiento, liberación de pedidos, disponibilidad, consumo y costo de recurso que varía en el tiempo, con el fin de minimizar tiempo de proceso y costo de producción; incluyó un proceso de ponderación para escoger la mejor secuencia de programación. Como aporte principal se propone una metodología novedosa que al compararla con otras metodologías encontradas en la bibliografía, demostró mejoras mayores al 10% en makespan y costo total del recurso consumidoAbstract: The study object of the present thesis is the flexible job shop in the metal mechanic sector. The research problem was derived from the systematic search of methodologies and algorithms to schedule production systems; configurations of process variables not addressed in the literature were identified, which is considered an empty in knowledge. Consequent with previous, a methodology was designed based on an evolutionary algorithm to schedule orders in a flexible job shop, with time restrictions, sequence, maintenance, liberation of orders, availability, consumption and cost of resource that varies in time, in order to minimize processing time and cost of production; it includes a weighting process to choose the best programming sequence. As main contribution a novel methodology was proposed which, compared with other methodologies found in the literature, it demonstrated greater improvements to 10% in Makespan and total cost of consumed resourceDoctorad