Analysis of a hybrid robot–operator kitting system in the automotive industry : design and optimal assignment of parts to pickers

Cette thèse, réalisée en collaboration avec le Groupe Renault dans le cadre d’un projet d’automatisation du kitting, s’intéresse à l’optimisation du processus de kitting en termes de maximisation du temps de cycle. Pour cela, nous étudions différentes configurations de système de kitting hybride avec robots(s) et opérateur(s) travaillant en série et séparés par un stock de découplage. Le(s) robot(s) commence(nt) la préparation des kits de pièces puis le(s) opérateur(s) se trouvant dans la partie manuelle du kitting récupère(nt) cette préparation et la complète(nt) avec les pièces affectées à cette zone.Notre objectif est de développer un outil d’aide à la décision permettant d’évaluer la performance d’un kitting hybride et de simuler son fonctionnement dans une configuration donnée (layout, politique de picking, etc.) avant son déploiement physique.Tout d’abord, à travers une modélisation des opérationsélémentaires de kitting effectuées par des robots et des opérateurs (prise et dépose, déplacement, etc.), nous proposons un modèle de temps de cycle permettant d’évaluer la performance du système hybride en termes de temps de cycle. Ensuite, nous développons un modèle d’affectation de pièces (PLMNE) permettant de les répartir entre kitting robotisé et manuel. L’objectif est de minimiser les temps de cycle et d’équilibrer la charge de travail entre les deux modes de kitting. Le modèle est appliqué à deux études de cas pratiques issues d’une usine Renault. Les résultats permettent d’identifier les paramètres qui impactent le plus les temps de cycle et le choix d’affectation des pièces entre kitting automatisé et manuel. Enfin, nous développons un modèle de simulation afin de calculer la taille optimale du stock de découplage entre kitting automatisé et manuel dans le but de maximiser la cadence du système hybride de kitting.In this thesis, conducted with Renault in the context of a kitting automation project, we are interested in the optimisation of kitting processes in terms of cycle time maximisation. To do so, we study different configurations of hybrid robot-operator kitting systems where robots (two types of robots considered) and operators are connected in series by an intermediate buffer (to decouple their activities). The robotic kitting area starts the preparation of kits then the operators in the manual kitting area retrieve the preparation of robots and complete with the remaining parts.Our objective is to develop a decision-making tool that assesses the hybrid system performance in a given configuration (layout, picking policy, etc.).First, through a modelling of elementary kitting operations performed by robots and operators (pick and place, travel, etc.), we develop a cycle time model to assess the performance of hybrid kitting systems. Then, we develop an assignment model that assigns parts (formulated as a mixed integer linear programming (MILP) problem) either to robotic or manual kitting areas with the objective of minimising cycle times and balancing workload between them. The model is applied to two case studies pertaining to a Renault plant. This analysis identifies the parameters that influence cycle times and the choice between robotic and manual kitting. Finally, we develop a simulation model to find the optimal buffer size between robotic and manual kitting so that throughput is maximised

Modeling kitting operations in a semi-robotic environment

International audienceWith increasing components variety in mixed-model assembly lines, kitting is an innovative line feeding mode to reduce congestion at the border of the line. This paper proposes a preliminary mathematical formulation of kitting activities for a hybrid robot-operator kitting system that delivers parts to a mixed-model assembly line. Indeed, elementary kitting operations are formulated, based on field assumptions, by distinguishing operations performed by the robot and the operator. Based on the formulation provided, the perspective of future research is to refine the model and to use the formulations in order to propose a quantitative model that would optimize the performance of the hybrid system

A mathematical model to assess the performance of a robotic kitting system in an assembly plant

International audienceOrder picking is the operation that consists in retrieving, from the storage locations, the parts needed for the assembly of final products. Making a ready-to-delivery collection or kit of parts is called Kitting. To improve this operation's performance, flexible robotic systems can greatly help industrials. Indeed, the technological advances that have been achieved in the recent years, in robotics and artificial intelligence make it possible to deal with a large range of items to be picked despite some remaining constraints related to components diversity and parts characteristics. In this paper, we study a robotic kitting system running with a robot arm mounted on a rail system and traveling along a narrow-aisle to pick parts. Through a modeling of elementary kitting operations that the robot performs (pick and place, travel, tool changing, etc.), we aim at evaluating the performance of the robotic kitting system in terms of cycle times. This study conducted with a manufacturer in the context of an ongoing project on automation of kitting operations, can help him to assess the robotic area performance in a given configuration (layout, picking policy, etc.)

Kitting optimisation in Just-in-Time mixed-model assembly lines: assigning parts to pickers in a hybrid robot–operator kitting system

International audienc