Incorporating working conditions to a mixed- model sequencing problem

Partiendo de una variante de un problema de secuenciación en líneas de productos mixtos (MMSP-W: Mixed-Model Sequencing Problem with Workload Minimisation), se proponen dos nuevos modelos que incorporan condiciones laborales a los puestos de trabajo de la línea. El primero tiene en cuenta la limitación de la saturación de los puestos de trabajo, mientras que el segundo contempla, además, la activación de los operarios a lo largo de la jornada laboral. Se realizan sendas experiencias computacionales, empleando un caso de estudio de la planta de motores de Nissan en Barcelona, con dos propósitos: (1) estudiar la repercusión que ocasiona la limitación de la saturación sobre la caída de la productividad de la línea, y (2) evaluar la recuperación de la productividad de la línea, mediante la activación de los operarios, manteniendo la misma calidad en las condiciones laborales conseguida al limitar la saturación.Beginning with a variation of the sequencing problem in a mixed-products line (MMSP-W: Mixed-Model Sequencing Problem with Workload Minimization), we propose two new models that incorporate the working conditions into the workstations on the line. The first model takes into account the saturation limit of the workstations, and the second model also includes the activation of the operators throughout the working day. Two computational experiments were carried out using a case study of the Nissan motor plant in Barcelona with two main objectives: (1) to study the repercussions of the saturation limit on the decrease in productivity on the line and (2) to evaluate the recovery of productivity on the line via activation of operators while maintaining the same quality in working conditions achieved by limiting the saturation. The obtained results show that the saturation limitation leads to suppose an important increase of work overload, which means average economic losses of 28,731.8 euros/day. However, the consideration of activity reduces these losses by 62.7%.Preprin

Free and regular mixed-model sequences by a linear program-assisted hybrid algorithm GRASP-LP

A linear program-assisted hybrid algorithm (GRASP-LP) is presented to solve a mixed-model sequencing problem in an assembly line. The issue of the problem is to obtain manufacturing sequences of product models with the minimum work overload, allowing the free interruption of operations at workstations and preserving the production mix. The implemented GRASP-LP is compared with other procedures through a case study linked with the Nissan’ Engine Plant from Barcelona.Peer ReviewedPostprint (author's final draft

Modeling and Solution Methodologies for Mixed-Model Sequencing in Automobile Industry

The global competitive environment leads companies to consider how to produce high-quality products at a lower cost. Mixed-model assembly lines are often designed such that average station work satisfies the time allocated to each station, but some models with work-intensive options require more than the allocated time. Sequencing varying models in a mixed-model assembly line, mixed-model sequencing (MMS), is a short-term decision problem that has the objective of preventing line stoppage resulting from a station work overload. Accordingly, a good allocation of models is necessary to avoid work overload. The car sequencing problem (CSP) is a specific version of the MMS that minimizes work overload by controlling the sequence of models. In order to do that, CSP restricts the number of work-intensive options by applying capacity rules. Consequently, the objective is to find the sequence with the minimum number of capacity rule violations. In this dissertation, we provide exact and heuristic solution approaches to solve different variants of MMS and CSP. First, we provide five improved lower bounds for benchmark CSP instances by solving problems optimally with a subset of options. We present four local search metaheuristics adapting efficient transformation operators to solve CSP. The computational experiments show that the Adaptive Local Search provides a significant advantage by not requiring tuning on the operator weights due to its adaptive control mechanism. Additionally, we propose a two-stage stochastic program for the mixed-model sequencing (MMS) problem with stochastic product failures, and provide improvements to the second-stage problem. To tackle the exponential number of scenarios, we employ the sample average approximation approach and two solution methodologies. On one hand, we develop an L-shaped decomposition-based algorithm, where the computational experiments show its superiority over solving the deterministic equivalent formulation with an off-the-shelf solver. We also provide a tabu search algorithm in addition to a greedy heuristic to tackle case study instances inspired by our car manufacturer partner. Numerical experiments show that the proposed solution methodologies generate high-quality solutions by utilizing a sample of scenarios. Particularly, a robust sequence that is generated by considering car failures can decrease the expected work overload by more than 20\% for both small- and large-sized instances. To the best of our knowledge, this is the first study that considers stochastic failures of products in MMS. Moreover, we propose a two-stage stochastic program and formulation improvements for a mixed-model sequencing problem with stochastic product failures and integrated reinsertion process. We present a bi-objective evolutionary optimization algorithm, a two-stage bi-objective local search algorithm, and a hybrid local search integrated evolutionary optimization algorithm to tackle the proposed problem. Numerical experiments over a case study show that while the hybrid algorithm provides a better exploration of the Pareto front representation and more reliable solutions in terms of waiting time of failed vehicles, the local search algorithm provides more reliable solutions in terms of work overload objective. Finally, dynamic reinsertion simulations are executed over industry-inspired instances to assess the quality of the solutions. The results show that integrating the reinsertion process in addition to considering vehicle failures can keep reducing the work overload by around 20\% while significantly decreasing the waiting time of the failed vehicles

Mixed-model Sequencing with Reinsertion of Failed Vehicles: A Case Study for Automobile Industry

In the automotive industry, some vehicles, failed vehicles, cannot be produced according to the planned schedule due to some reasons such as material shortage, paint failure, etc. These vehicles are pulled out of the sequence, potentially resulting in an increased work overload. On the other hand, the reinsertion of failed vehicles is executed dynamically as suitable positions occur. In case such positions do not occur enough, either the vehicles waiting for reinsertion accumulate or reinsertions are made to worse positions by sacrificing production efficiency. This study proposes a bi-objective two-stage stochastic program and formulation improvements for a mixed-model sequencing problem with stochastic product failures and integrated reinsertion process. Moreover, an evolutionary optimization algorithm, a two-stage local search algorithm, and a hybrid approach are developed. Numerical experiments over a case study show that while the hybrid algorithm better explores the Pareto front representation, the local search algorithm provides more reliable solutions regarding work overload objective. Finally, the results of the dynamic reinsertion simulations show that we can decrease the work overload by ~20\% while significantly decreasing the waiting time of the failed vehicles by considering vehicle failures and integrating the reinsertion process into the mixed-model sequencing problem.Comment: 26 pages, 6 figures, 5 table

An expert system to minimize operational costs in mixed-model sequencing problems with activity factor

One of the major issues in industrial environments is currently maximizing productivity while reducing manufacturing cost. This can be seen clearly reflected in mixed-model assembly lines based systems, where obtaining efficient manufacturing sequences is a key to be competitive in a dynamic and globalized market. However, this continuous cost reduction and productivity growth should not penalize the welfare of employees. This work is intended to address this lack of compatibility between the economic and social objectives through the study of the mixed-model sequencing problem from both the business and labor perspective. This is done by considering the possibility of reducing or increasing processing times of operations by varying the work pace of line's operators within the permissible legal boundaries. Thus, depending on this flexible activation time of operators, the amount of completed work and idle time will be one or the other and, consequently, the productivity of the line will also improve or get worse. In this regard, we propose new approach to the sequencing problem without incurring cost increases and providing a safe working environment, in accordance with applicable law. This new approach leads to obtain efficient manufacturing sequences, in terms of both productivity and labor conditions. Specifically, the objective of the new problem is minimizing the unproductive costs of the line by incorporating the possibility of increasing production through the variation of the work pace of line's operators. Increasing the work pace of operators, the amount of non-completed work or the preventable idle time can be reduced and therefore, their associated costs too. In addition, and without losing sight of the effort involved in working with a work pace above the normal, we propose several economic criteria to compensate the activation of workers where necessaryPeer ReviewedPostprint (author's final draft

A hybrid dynamic programming for solving a mixed-model sequencing problem with production mix restriction and free interruptions

In this article, we propose a hybrid procedure based on bounded dynamic programming assisted by linear programming to solve the mixed-model sequencing problem with workload minimization with serial workstations, free interruption of the operations and with production mix restrictions. We performed a computational experiment with 23 instances related to a case study of the Nissan powertrain plant located in Barcelona. The results of our proposal are compared with those obtained by mixed integer linear programming.Peer ReviewedPostprint (author's final draft

Productivity improvement, considering legal conditions and Just In Time principles in the mixed-model Sequencing problem

A new mathematical model to solve the Mixed-Model Sequencing Problem with Work overload minimization is formulated. The model incorporates productive, social and legal aspects in order to move the theory problem closer to the actual industrial environments. Specifically, there are considered the variation of work pace of workers throughout the workday to increase the completed work; the conditions of occupancy level of workers imposed by the collective agreements; and the idea of keeping constant the production mix through the sequence leading both to a balance between the required workloads at stations and regular consumption of components. Indeed, by means of a case study linked to Nissan, a gain of over 98% is achieved in terms of regular cumulative production and required work, while performing the 100% of required work and following legal restrictions of operators’ saturation.Postprint (published version

Consideration of human resources in the Mixed-model Sequencing Problem with Work Overload Minimization: Legal provisions and productivity improvement

Beginning with a variation of the sequencing problem in a mixed-products line (MMSP-W: Mixed-Model Sequencing Problem with Workload Minimization), we propose two new models that incorporate a set of working conditions in regard with human resources of workstations on the line. These conditions come from collective agreements and therefore must be respected by both company and labor unions. The first model takes into account the saturation limit of the workstations, and the second model also includes the activation of the operators throughout the working day. Two computational experiments were carried out using a case study of the Nissan motor plant in Barcelona with two main objectives: (1) to study the repercussions of the saturation limit on the decrease in productivity on the line and (2) to evaluate the recovery of productivity on the line via both activation of operators, while maintaining the same quality in working conditions achieved by limiting the saturation, and auxiliary processors. By results we state that saturation limitation leads an important increase of work overload, which means average economic losses of 28,731.8 Euros/day. However, the productivity reduction may be counteracted by the work pace factor increase, at certain moments of workday, and/or by the incorporation of auxiliary processors into the line.Postprint (author's final draft

Incorporando regularidad del trabajo requerido al MMSP con mínima sobrecarga.

Se presenta un modelo matemático para una variante del problema Mixed - Model Sequencing ( MMSP ) minimizando la sobrecarga y manteniendo constante la tasa del trabajo requerido. Se realiza un exper i mento con ejemplares de ref e rencia de la literatura empleando Programación Lineal Entera MixtaPostprint (published version