Showing papers by "Jean-Pierre Kenné published in 2011"
TL;DR: The objective of the study is to find the decision variables that minimize the overall cost, including repair, replacement, preventive maintenance, inventory holding and backlog costs over an infinite planning horizon.
83 citations
TL;DR: An integrated mathematical model leading to information sharing strategies for supplier selection, replenishments and production activities and shows clearly that it is always profitable to consider multiple suppliers to make replenishment and production decisions.
45 citations
TL;DR: In this paper, a special case of integration of preventive maintenance into the repair/replacement policy of a failure-prone system is presented, where the machine of the considered system exhibits increasing failure intensity and increasing repair times.
Abstract: This paper presents a special case of integration of the preventive maintenance into the repair/replacement policy of a failure-prone system. The machine of the considered system exhibits increasing failure intensity and increasing repair times. To reduce the failure rate and subsequent repair times following a failure, there is an incentive to perform preventive maintenance on the machine before failure. When a failure occurs, the machine can be repaired or replaced by a new one. Thus the machine's mode at any time can be classified as either operating, in repair, in replacement or in preventive maintenance. The decision variables of the system are the repair/replacement switching age or number of failures at the time of the machine's failure and the preventive maintenance rate. The problem of determining the repair/replacement and preventive maintenance policies is formulated as a semi-Markov decision process and numerical methods are given in order to compute optimal policies which minimise the average...
25 citations
TL;DR: In this article, a semi-Markov decision process is used to describe the dynamics of a deteriorating production system subject to random machine breakdowns, repair and replacement activities, and the objective of the study is to find the decision variables that minimize the overall cost, including repair, replacement, inventory holding, and backlog costs.
Abstract: In this paper, a deteriorating production system subject to random machine breakdowns, repair and replacement activities, is investigated. The machine manufactures one type of product, and when a breakdown occurs, either a repair or a replacement action is chosen. The machine is replaced with a new one if the replacement option is selected, and no repair action is considered in such a situation. The decision variables of the control problem are the production rate and the repair/replacement switching policy upon machine failure. The objective of the study is to find the decision variables that minimize the overall cost, including repair, replacement, inventory holding, and backlog costs, over an infinite planning horizon. This paper differs from similar research projects in that it considers the fact that machine repair activities depend on the repair history, and a semi-Markov decision process is used to describe the dynamics of the system. The proposed optimality conditions are developed using the stochastic dynamic programming approach, with a numerical example given to illustrate the utility of the proposed approach, and a sensitivity analysis considered to confirm the structure of the control policy obtained.
24 citations
22 citations
TL;DR: Simulated and experimental results show that the controller was able to maneuver the proposed ExoRob efficiently in order to track the desired trajectories, which in this case consisted in passive arm movements, which are widely used in therapy and were performed efficiently with the developed model and controller.
Abstract: Proper functioning of the shoulder, elbow, and wrist movements play a vital role in the performance of essential daily activities. To assist physically disabled people with impaired upper-limb function, we have been developing an exoskeleton robot (ExoRob) to rehabilitate and to ease upper limb motion. The proposed ExoRob will be comprised of seven degrees of freedom (DOFs) to enable natural movements of the human upper-limb. This paper focuses on the kinematic and dynamic modeling of the proposed ExoRob that corresponds to human upper-limbs. For this purpose, a nonlinear computed torque control technique was employed. In simulations, trajectory tracking corresponding to typical rehabilitation exercises were carried out to evaluate the performances of the developed model and controller. For the experimental part, only 3DOFs (elbow, wrist flexion/extension, wrist abduction/adduction) were considered. Simulated and experimental results show that the controller was able to maneuver the proposed ExoRob efficiently in order to track the desired trajectories, which in this case consisted in passive arm movements. Such movements are widely used in therapy and were performed efficiently with the developed ExoRob and the controller.
18 citations
TL;DR: In this article, a 2DOF exoskeleton robot (ExoRob) is used to provide naturalistic range movements of elbow (flexion/extension) and forearm (pronation/supination) motions.
Abstract: The movements of the shoulder, elbow, and wrist play a vital role in the performance of essential daily activities. We therefore have developed a 2DOF exoskeleton robot ( ExoRob ) to rehabilitate the elbow and forearm movements of physically disabled individuals with impaired upper-limb function. The proposed ExoRob is supposed to be worn on the lateral side of forearm in order to provide naturalistic range movements of elbow (flexion/extension) and forearm (pronation/supination) motions. This paper focuses on the modelling, design (electrical and mechanical components), development, and control of the proposed ExoRob . The kinematic model of ExoRob has been developed based on modified Denavit-Hartenberg notations. Non-linear modified computed torque control technique is employed to control the proposed ExoRob , where trajectories (i.e., pre-programmed trajectories recommended by therapist/clinician) tracking corresponding to typical rehabilitation (passive) exercises has been carried out to evaluate the performances of the developed ExoRob and controller. Furthermore, experiments were carried out with the master exoskeleton arm [ mExoArm , an upper-limb prototype 7DOF (lower scaled) exoskeleton arm] where subjects (robot users) or experimenter operate the mExoArm (like a joystick) to manoeuvre the proposed ExoRob to provide passive rehabilitation. Experimental results show that the controller is able to manoeuvre the ExoRob efficiently to track the desired trajectories. Such movements are widely used in rehabilitation and have been performed efficiently with the developed ExoRob and the controller.
17 citations
TL;DR: This study seeks to identify optimal costs related to backlogs, inventories and maintenance over an infinite planning horizon, along with levels of occupational risk where production control includes efficient planning of lockouts/tagouts, and offers numerical methods which may be employed to achieve optimal conditions in setting control policies.
14 citations
TL;DR: In this article, an optimal stochastic control model where interactive feedback consists of the quantity of flawless and defective products was developed to minimize the expected discounted overall cost due to maintenance activities, inventory holding and backlogs.
Abstract: Purpose – This paper seeks to develop an optimal stochastic control model where interactive feedback consists of the quantity of flawless and defective products. The main objective of this study is to minimize the expected discounted overall cost due to maintenance activities, inventory holding and backlogs.Design/methodology/approach – The model differs from similar research projects in that, instead of age‐dependent machine failure, it considers only defective products as feedback into the optimal model for maintenance and production planning. In this paper a near optimal control policy of the system through numerical techniques is obtained.Findings – In this paper, a new model in which the system's retroaction is the quantity of defective products is presented, considering that defective products are a consequence of global manufacturing system deterioration. Instead of taking into account machine failure and human error separately, it considers a defect in product as being the consequence of a combine...
13 citations
15 Jun 2011
TL;DR: In this article, a two-level hierarchical decision-making approach is proposed to minimize a discounted overall cost consisting of preventive and corrective maintenance costs, inventory holding cost and backlog cost.
Abstract: This paper deals with the joint analysis of the optimal production and maintenance planning problems for a manufacturing system subject to random failures and repairs. When a machine fails down, an imperfect corrective maintenance is undertaken. The objective of this study is to minimize a discounted overall cost consisting of preventive and corrective maintenance costs, inventory holding cost and backlog cost. A two-level hierarchical decision making approach, based on the determination of the mean time to failure (first level) and the statement of a joint optimization of production, preventive and corrective maintenance policies (second level) is proposed. Hence the production, preventive and corrective maintenance rates are determined in the second level given the failure rates obtained from the first level. In the proposed model, the failure rate of the machine depends on the number of failures; hence, the control policies of the considered planning problems depend on the number of failures. A numerical example and a sensitivity analysis will illustrate the structure of the optimal control policies and the usefulness on the proposed approach.
3 citations
01 Jan 2011
TL;DR: In this article, a two-level hierarchical control model is developed for a reliable single-product manufacturing system with a finite capacity, where the demand by customers is stochastic in a finite planning horizon, and is described by a known continuous function.
Abstract: This paper addresses a stochastic optimal control problem for a reliable single-product manufacturing system with a finite capacity. The demand by customers is stochastic in a finite planning horizon, and is described by a known continuous function. A two-level hierarchical control model is developed. In the first level, a stochastic linear-quadratic optimal control problem is formulated to determine the target values of the state and control variables, with the variables being the desired inventory level and desired production rate, respectively. The goal of the second level is to maintain the inventory as close as possible to its desired level as well as to maintain the production rate as close as possible to its desired rate with fluctuating demand. This problem is represented as a recursive optimization control problem (predictive control) with one state variable (the inventory level) and one control variable (the production rate). The purpose of this study is to establish the optimal production control strategies satisfying a stochastic demand that minimizes the total average quadratic cost and the sum of the mean square deviations of inventory and production for the first and second levels, respectively. The solution is obtained by applying the stochastic optimal control principle based on Pontryagin’s maximum principle using the Euler-Maruyama scheme. A numerical example and sensitivity analyses are presented to illustrate the usefulness of the proposed approach.