UML based reconfiguration rate analysis of assembly line depending on robot integration

Factories with a high production throughput and a low product variety traditionally choose a flow layout for mass production. The future market profile however will be volatile, customers expecting a larger choice in product diversity. Such a variable demand calls a new, flexible and reconfigurable production system, able to reconfigure in order to follow the market. This paper aims to present a method to modelize the production system permitting to identify the ways of improving the facilities on the reconfigurability criterion. Several reconfigurable assembly systems are proposed, targeting full load of the facilities. The specificity of the study consists in the consideration of both multiproduct and volume flexibility

Identification of reconfigurability enablers and weighting of reconfigurability characteristics based on a case study

Today manufacturing systems face a volatile demand with varying customer needs in terms of both volume and product mix ratio. The highly automated dedicated production lines can not fulfil the demand diversity which needs quick adaptation of the production system. Market fluctuations for the next years are unknown and products have shorter lifecycles. In order to specify precisely needs of factories regarding flexibility, this paper presents a methodology using a qualitative analysis and its application to a use case company. The aim is identification of current needs regarding reconfigurability of production systems and following research directions. To do so, decision makers from various fields and decision levels are identified and interviewed individually using a questionnaire. An Analytic Hierarchy Process (AHP) is also applied to identify weights of the six characteristics of reconfigurability: modularity, integrability, customization, convertibility, scalability and diagnosability; based on the experience of the interviewed decision-makers. Indeed, there is no standardized reconfigurability indicator for the assessment of a production system regarding its changeability capacity. Weighting of these characteristics is the first step before computing numerical values for each characteristic based on a mathematical model proposed in literature

Framework for the design and evaluation of a reconfigurable production system based on movable robot integration

Enterprises now face a global, dynamic, and unpredictable economic environment. In response to quick changes of the demand, the production needs to have the ability to adapt rapidly to meet the production requirements. The Reconfigurable Manufacturing System (RMS) paradigm enables such capabilities. However, defining design and reconfiguration rules is highly challenging, as it requires a broad knowledge encompassing the inclusion of technological, production, and economic metrics, as well as an understanding of a reconfiguration strategy, determining the necessary reconfiguration frequency of the system. For now, no global methodology taking all those aspects into account has been proposed. This article presents an original framework for the design, evaluation, and reconfiguration of the Reconfigurable Production System (RPS). New metrics to measure reconfigurability are defined. The design approach consists in three main steps which are individually developed. The selection of the appropriated production system is based on the comparison of reconfigurability and productivity indicators. Finally, the reconfiguration strategy is presented. The methodology is applied on a case study from the automotive industry

Risk and decision analysis for Reconfigurable Assembly System Design under uncertainties

To face the variable demand of the market, modular and mobile equipment are integrated on production lines. Previous works proposed design and evaluation methodologies to build recon figurable production systems. However, taking the right decision concerning investments and the choice of equipment may be complex. In this paper, we present RAS design from a risk and decision analysis perspective to support decision making. Market demand scenarios are associated with occurrence probabilities. A decision tree represents consecutive scenarios, for which the decision maker is proposed to make a choice regarding investments for the assembly line. The utility function is computed based on the decision maker as attitude to risk. The objective function computing the final score of a scenario and a decision covers investments, recon figurability rate and performance of the system. Implications of early investments towards recon gurability can be identi ed. The approach is applied on a real use case from the automotive industry

Analyse du taux de reconfiguration d’une ligne d’assemblage par intégration de modules robotisés via une modélisation par diagramme UML de classes

Le système de production le plus utilisé dans l’industrie dans le cas d’un fort volume est le flow layout. Cependant, le marché futur s’annonce imprévisible et volatile, tiré par une demande client tendant vers des produits toujours plus adaptés à leurs besoins et personnalisables, ce qui correspond à un plus grand choix de diversité produit. Une telle variabilité du marché nécessite de repenser le système de production afin qu’il soit agile, reconfigurable, et capable d’être transformé afin de suivre la demande du marché. L’objet de cet article est dans un premier temps l’identification des limites à la transformabilité du système actuel, puis l’élaboration d’un méta-modèle, utilisant le diagramme de classes UML (Unified Modeling Language) , permettant de décrire les éléments physiques d’un système reconfigurable. Différentes solutions de reconfigurabilité, sur la base de l’intégration de modules robotisés, sont ainsi représentées et évaluées qualitativement relativement à la flexibilité volume et à la flexibilité des familles de produits

Simulation-based optimization approach with scenario-based product sequence in a Reconfigurable Manufacturing System (RMS): A case study

In this study, we consider a production planning and resource allocation problem of a Reconfigurable Manufacturing System (RMS). Four general scenarios are considered for the product arrival sequence. The objective function aims to minimize total completion time of jobs. For a given set of input parameters defined by the market, we want to find the best configuration for the production line with respect to the number of resources and their allocation on workstations. In order to solve the problem, a hybridization approach based on simulation and optimization (Sim-Opt) is proposed. In the simulation phase, a Discrete Event Simulation (DES) model is developed. On the other hand, a simulated annealing (SA) algorithm is developed in Python to optimize the solution. In this approach, the results of the optimization feed the simulation model. On the other side, performance of these solutions are copied from simulation model to the optimization model. The best solution with the best performance can be achieved by this manually cyclic approach. The proposed approach is applied on a real case study from the automotive industry

Hybrid optimisation approach for sequencing and assignment decision-making in reconfigurable assembly line

Technological advances, promoted by the Industry 4.0 paradigm, attempt to support the recon gurability of manufacturing systems and to contribute to adaptive operational conditions. These systems must be responsive to signi cant changes in demand volume and product mix. In this paper, a hybrid optimisation approach is suggested to solve sequencing and assignment problems of recon gurable assembly lines, where mobile robots collaborate with human operators. The objectives are: i) to de ne a schedule of jobs, ii) to assign tasks to the mobile robots, and iii) to decide the allocation of robots to workstations, in order to minimise the number of robots required. Preliminary results show that the proposed methodology can make an efficient robot allocation under high demand variety. In addition to that, the hybrid optimisation approach can be adapted to other con gurations of assembly systems, which demonstrates its applicability to solve problems in other contexts