Planification socio-responsable du travail dans les chaînes de montage d'aéronefs : comment satisfaire à la fois objectifs ergonomiques et économiques

Dans cette thèse, le problème de planification des tâches dans les chaînes de montage des aéronefs est étudié. Ces lignes de production sont principalement manuelles et tactées. L'échec de la livraison dans les délais pouvant entraîner des pénalités importantes pour le fabricant, il est essentiel de respecter le calendrier de chaque poste de travail en tenant compte à la fois de critères économiques et ergonomiques. Ce problème de planification peut être considéré comme un problème généralisé de planification de projets avec contraintes de ressources (RCPSP). Dans un premier temps, nous passons en revue les méthodes ergonomiques existantes qui peuvent être utilisées pour évaluer la charge de travail physique dans les lignes de production et examinons leur applicabilité au contexte des chaînes de montage d'aéronefs avec des temps de cycle longs. Sur la base de cette évaluation, nous développons des modèles mathématiques à introduire dans les problèmes considérés du RCPSP afin de prendre en compte l'impact ergonomique sur les opérateurs. Tenant compte de ces contraintes ergonomiques, le problème industriel initial est modélisé comme un RCPSP avec des contraintes et des objectifs spéciaux intégrant à la fois des aspects économiques et ergonomiques. Plusieurs formulations avec des opérateurs polyvalents, des ressources avec des capacités dépendantes du temps, des contraintes sur les facteurs ergonomiques et des tâches multimodales ordonnées par des relations de précédence complexes sont considérées. Des modèles de programmation par contraintes et de programmation linéaire en nombres entiers ont été développés pour ces formulations. Afin d'améliorer les procédures de solution, de nouvelles techniques de propagation de contraintes sont proposées et mises en œuvre. Un nouvel algorithme pour le calcul de la borne inférieure est également développé. L'efficacité des modèles et méthodes présentés est validée par des expériences numériques.In this thesis, the scheduling problem of tasks in aircraft assembly lines is studied. These production lines are mainly manual and paced. Since the failure of delivery on time may result in significant penalties for the manufacturer, it is crucial to meet the schedule at each workstation taking into account both economic and ergonomic criteria. This scheduling problem can be considered as a generalized Resource-Constraints Project Scheduling Problem (RCPSP). Firstly, we review the existing ergonomic methods that can be used to evaluate the physical workload in production lines and examine their applicability to the context of aircraft assembly lines with long takt times. On the basis of this evaluation, we develop mathematical models to be introduced in considered RCPSP problems in order to take into account the ergonomic impact on the operators. Taking into consideration these ergonomic constraints, the original industrial problem is modeled as a RCPSP with special constraints and objectives integrating both economic and ergonomic aspects. Several formulations with multi-skilled operators, resources with time-dependent capacities, constraints on ergonomic factors and multi-mode tasks ordered by precedence relations with time lags are considered. Constraint Programming and Integer Linear Programming models are developed for these formulations. In order to enhance the solution procedures, novel constraint propagation techniques are proposed and implemented. A new algorithm for lower bound calculation is developed as well. The efficiency of presented models and methods are validated through numerical experiments

A MILP model for an integrated project scheduling and multi-skilled workforce allocation with flexible working hours

In this paper, we integrate two decision problems arising in various applications such as production planning and project management: the project scheduling problem, which consists in scheduling a set of precedence-constrained tasks, where each task requires executing a set of skills to be performed, and the workforce allocation problem which includes assigning workers as scarce resources to the skills of each task. These two problems are interrelated as the tasks durations are not predefined, but depend on the number of workers assigned to that task as well as their skill levels. We here present a mixed integer linear programming model that considers important real life aspects related to the flexibility in the use of human resources, such as multi-skilled workers whose skill levels are different and measured by their efficiencies. Hence, execution times of the same workload by different workers vary according to these efficiencies. Moreover, the model considers the flexible working time of employees; i.e. the daily and weekly workload of a given worker may vary from one period to another according to the work required. Furthermore, efficient team building is incorporated in this model; i.e. assigning an expert worker and one or more apprentice worker(s) together with the purpose of skill development thanks to knowledge transfer. A numerical example is provided to check the performance of the model

An analysis of task assignment and cycle times when robots are added to human-operated assembly lines, using mathematical programming models

Abstract Adding robots to a human-operated assembly line influences both the short- and long-term operation of the line. However, the effects of robots on assembly line capacity and on cycle time can only be studied if appropriate task assignment models are available. This paper shows how traditional assembly line balancing models can be changed in order to determine the optimal number of workstations and cycle time when robots with different technological capabilities are able to perform a predetermined set of tasks. The mathematical programming models for the following three cases are presented and analysed: i) only workers are assigned to the workstations; ii) either a worker or a robot is assigned to a workstation; iii) a robot and a worker are also assigned to specific workstations. The data of an assembly line producing power inverters is used to illustrate the proposed calculations. Both the assignment of tasks and the changes of cycle time are analysed within the AIMMS modelling environment. The computational characteristics of the proposed mathematical programming models are also examined and tested using benchmark problems. The models presented in this paper can assist operations management in making decisions relating to assembly line configuration

Flexible Job-shop Scheduling Problem with Sequencing Flexibility: Mathematical Models and Solution Algorithms

Marketing strategists usually advocate increased product variety to attend better market demand. Furthermore, companies increasingly acquire more advanced manufacturing systems to take care of the increased product mix. Manufacturing resources with different capabilities give a competitive advantage to the industry. Proper management of the current productions resources is crucial for a thriving industry. Flexible job shop scheduling problem (FJSP) is an extension of the classical Job-shop scheduling problem (JSP) where operations can be performed by a set of candidate capable machines. An extended version of the FJSP, entitled FJSP with sequencing flexibility (FJSPS), is studied in this work. The extension considers precedence between the operations in the form of a directed acyclic graph instead of sequential order. In this work, a mixed integer programming (MILP) formulation is presented. A single objective formulation to minimize the weighted tardiness for the FJSP with sequencing flexibility is proposed. A different objective to minimize makespan is also considered. Due to the NP-hardness of the problem, a novel hybrid bacterial foraging optimization algorithm (HBFOA) is developed to tackle the FJSP with sequencing flexibility. It is inspired by the behaviour of the E. coli bacteria. It mimics the process to seek for food. The HBFOA is enhanced with simulated annealing (SA). The HBFOA has been packaged in the form of a decision support system (DSS). A case study of a small and medium-sized enterprise (SME) manufacturing industry is presented to validate the proposed HBFOA and MILP. Additional numerical experiments with instances provided by the literature are considered. The results demonstrate that the HBFOA outperformed the classical dispatching rules and the best integer solution of MILP when minimizing the weighted tardiness and offered comparable results for the makespan instances. In this dissertation, another critical aspect has been studied. In the industry, skilled workers usually are able to operate a specific set of machines. Hence, managers need to decide the best operation assignments to machines and workers. However, they need also to balance the workload between workers while accomplishing the due dates. In this research, a multi-objective mathematical model that minimizes makespan, maximal worker workload and weighted tardiness is developed. This model is entitled dual-resource FJSP with sequencing flexibility (DRFJSPS). It covers both the machine assignment and also the worker selection. Due to the intractability of the DRFJSPS, an elitist non-dominated sorting genetic algorithm (NSGA-II) is developed to solve this problem efficiently. The algorithm provides a set of Pareto-optimal solutions that the decision makers can use to evaluate the trade-offs of the conflicting objectives. New instances are introduced to demonstrate the applicability of the model and algorithm. A multi-random-start local search algorithm has been developed to assess the effectiveness of the adapted NSGA-II. The comparison of the solutions demonstrates that the modified NSGA-II provides a non-dominated efficient set in a reasonable time. Finally, a situation where there are multiple process plans available for a specific job is considered. This scenario is useful to be able to react to the current status of the shop where unpredictable circumstances (machine breakdown, current product mix, due dates, demand, etc.) can be accurately tackled. The determination of the process plan also depends on its cost. For that, a balance between cost, and the accomplishment of due dates is required. A multi-objective mathematical model that minimizes makespan, total processing cost and weighted tardiness are proposed to determine the sequence and the process plan to be used. This model is entitled flexible job-shop scheduling problem with sequencing and process plan flexibility (FJSP-2F). New instances are generated to show the applicability of the model

Aggregate assembly process planning for concurrent engineering

In today's consumer and economic climate, manufacturers are finding it increasingly difficult to produce finished products with increased functionality whilst fulfilling the aesthetic requirements of the consumer. To remain competitive, manufacturers must always look for ways to meet the faster, better, and cheaper mantra of today's economy. The ability for any industry to mirror the ideal world, where the design, manufacturing, and assembly process of a product would be perfected before it is put mto production, will undoubtedly save a great deal of time and money. This thesis introduces the concept of aggregate assembly process planning for the conceptual stages of design, with the aim of providing the methodology behind such an environment. The methodology is based on an aggregate product model and a connectivity model. Together, they encompass all the requirements needed to fully describe a product in terms of its assembly processes, providing a suitable means for generating assembly sequences. Two general-purpose heuristics methods namely, simulated annealing and genetic algorithms are used for the optimisation of assembly sequences generated, and the loading of the optimal assembly sequences on to workstations, generating an optimal assembly process plan for any given product. The main novelty of this work is in the mapping of the optimisation methods to the issue of assembly sequence generation and line balancing. This includes the formulation of the objective functions for optimismg assembly sequences and resource loading. Also novel to this work is the derivation of standard part assembly methodologies, used to establish and estimate functional tunes for standard assembly operations. The method is demonstrated using CAPABLEAssembly; a suite of interlinked modules that generates a pool of optimised assembly process plans using the concepts above. A total of nine industrial products have been modelled, four of which are the conceptual product models. The process plans generated to date have been tested on industrial assembly lines and in some cases yield an increase in the production rate

Impacto de la curva de aprendizaje en la fecha de terminación de pedidos en una línea a pulso

Las empresas de fabricación que trabajan en la industria aeronáutica cuentan con un límite de tiempo que deben cumplir para satisfacer las necesidades de la demanda, este límite se conoce como Takt Time. Gracias al aprendizaje obtenido por los operarios tras realizar las tareas es posible reducir el tiempo que emplean en hacer dichas tareas, con lo que es posible terminar los trabajos antes del Takt Time. Esta reducción en los tiempos es fundamental debido a que permite mejoras, puesto que en el mismo tiempo pueden realizarse más unidades o incluso requerir una menor plantilla para realizar el mismo trabajo, pudiendo usar a los operarios sobrantes en otras tareas que requieran apoyo o dimensionar de forma más adecuada la plantilla. Por ello el objetivo del presente Trabajo Fin de Máster se centra en analizar el impacto que tiene el aprendizaje de los operarios en la reducción de tiempos en un sistema de producción a pulso en tres escenarios diferentes: minimizar el Cmax (tiempo en el que todas las tareas se han terminado de procesar), minimizar el número de trabajadores para un Takt Time dado y por último, equilibrar la carga de trabajo entre los operarios.Manufacturing companies working in the aerospace industry have a time constraint that must be accomplished to meet the needs of the demand, this limit is known as Takt Time. Due to the learning obtained by the operators after performing the tasks, it is possible to reduce the time that they use in doing such tasks, which make it possible to complete work before the Takt Time. This reduction in time is fundamental because it allows improvements, since at the same time can be realized more units or even require a smaller workforce to do the same work, being able to use surplus workers in other tasks that require support or sizing properly the staff. For this reason, the aim of this Master's Final Project is to analyze the impact of the learning of the workers on the reduction of time in a pulse production system in three different scenarios: minimize the Cmax (time in which all tasks have been processed), minimize the number of workers for a given Takt Time and finally, balance the workload between the operators.Universidad de Sevilla. Máster en Organización Industrial y Gestión de Empresa

Simulation and optimization model for the construction of electrical substations

One of the most complex construction projects is electrical substations. An electrical substation is an auxiliary station of an electricity generation, transmission and distribution system where voltage is transformed from high to low or the reverse using transformers. Construction of electrical substation includes civil works and electromechanical works. The scope of civil works includes construction of several buildings/components divided into parallel and overlapped working phases that require variety of resources and are generally quite costly and consume a considerable amount of time. Therefore, construction of substations faces complicated time-cost-resource optimization problems. On another hand, the construction industry is turning out to be progressively competitive throughout the years, whereby the need to persistently discover approaches to enhance construction performance. To address the previously stated afflictions, this dissertation makes the underlying strides and introduces a simulation and optimization model for the execution processes of civil works for an electrical substation based on database excel file for input data entry. The input data include bill of quantities, maximum available resources, production rates, unit cost of resources and indirect cost. The model is built on Anylogic software using discrete event simulation method. The model is divided into three zones working in parallel to each other. Each zone includes a group of buildings related to the same construction area. Each zone-model describes the execution process schedule for each building in the zone, the time consumed, percentage of utilization of equipment and manpower crews, amount of materials consumed and total direct and indirect cost. The model is then optimized to mainly minimize the project duration using parameter variation experiment and genetic algorithm java code implemented using Anylogic platform. The model used allocated resource parameters as decision variables and available resources as constraints. The model is verified on real case studies in Egypt and sensitivity analysis studies are incorporated. The model is also validated using a real case study and proves its efficiency by attaining a reduction in model time units between simulation and optimization experiments of 10.25% and reduction in total cost of 4.7%. Also, by comparing the optimization results by the actual data of the case study, the model attains a reduction in time and cost by 13.6% and 6.3% respectively. An analysis to determine the effect of each resource on reduction in cost is also presented

Analysis and Optimization of Mobile Business Processes

Mobility of workers and business processes rapidly gains the attention of businesses and business analysts. A wide variety of definitions exists for mobile business processes. This work considers a type of business processes concerned with the maintenance of distributed technical equipment as, e.g., telecommunication networks, utility networks, or professional office gear. Executing the processes in question, workers travel to the location where the equipment is situated and perform tasks there. Depending on the type of activities to be performed, the workers need certain qualifications to fulfill their duty. Especially in network maintenance processes, activities are often not isolated but depend on the parallel or subsequent execution of other activities at other locations. Like every other economic activity, the out- lined mobile processes are under permanent pressure to be executed more efficiently. Since business process reengineering (BPR) projects are the common way to achieve process improvements, business analysts need methods to model and evaluate mobile business processes. Mobile processes challenge BPR projects in two ways: (i) the process at- tributes introduced by mobility (traveling, remote synchronization, etc.) complicate process modeling, and (ii) these attributes introduce process dynamics that prevent the straightforward prediction of BPR effects. This work solves these problems by developing a modeling method for mobile processes. The method allows for simulating mobile processes considering the mobility attributes while hiding the complexity of these attributes from the business analysts modeling the processes. Simulating business processes requires to assign activites to workers, which is called scheduling. The spatial distribution of activities relates scheduling to routing problems known from the logistics domain. To provide the simula- tor with scheduling capabilities the according Mobile Workforce Scheduling Problem with Multitask-Processes (MWSP-MP) is introduced and analyzed in-depth. A set of neighborhood operators was developed to allow for the application of heuristics and meta-heuristics to the problem. Furthermore, methods for generating start solutions of the MWSP-MP are introduced. The methods introduced throughout this work were validated with real-world data from a German utility. The contributions of this work are a reference model of mobile work, a business domain independent modeling method for mobile business processes, a simulation environment for such processes, and the introduction and analysis of the Mobile Workforce Scheduling Problem with Multitask-Processes

Scheduling and shop floor control in commercial airplane manufacturing

Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering; in conjunction with the Leaders for Manufacturing Program at MIT, 2005.Includes bibliographical references (p. 73-75).Boeing is the premier manufacturer of commercial jetliners and a leader in defense and space systems. Competition in commercial aircraft production is increasing and in order to retain their competitive position, Boeing must strive to improve their operations by reducing costs. Boeing factories today still schedule and monitor the shop floor much as they have for the past 100 years. This thesis compares and contrasts several different methods for shop floor control and scheduling including Boeing's barcharts, Toyota production system, critical chain, and dynamic scheduling. Each system is will be analyzed with respect to how it handles variability in labor output required and how that affects which products are typically made under each system. In additional to qualitative comparisons, discrete event simulations comparing the various strategies will be presented. Areas for future simulation study are also discussed. The recommended approach for commercial airplane assembly is critical chain. A suggested implementation plan is presented along with methods to ease acceptance.by Vikram Neal Sahney.S.M.M.B.A