Joint quality control and preventive maintenance strategy for imperfect production processes

In this paper, we develop a joint quality control and preventive maintenance policy for a production system producing conforming and nonconforming units. The considered system consists of one machine which must supply another production line operating on a just-in-time basis. Each lot produced by the machine is subject to a quality control. According to the proportion l of nonconforming units observed and compared to a threshold value l _m , one decides to undertake or not maintenance actions on the system. In order to palliate perturbations caused by the stopping of the machine for preventive and corrective maintenance actions of random durations, a buffer stock h is built up to ensure the continuous supply of the subsequent production line. The proposed strategy is modelled using simulation and experimental design. This approach allows to generate a second order response surface allowing to easily determine the optimal rate, l_m^*{l_{m}^*}, of nonconforming units on the basis of which preventive maintenance actions should be performed, and the optimal size, h*, of the buffer stock to be built. These values minimize the total cost per time unit which includes the costs related to maintenance, quality and inventory.     

Periodic and sequential preventive maintenance policies over a finite planning horizon with a dynamic failure law

The purpose of this study is to propose and model periodic and sequential preventive maintenance policies for a system that performs various missions over a finite planning horizon. Each mission can have different characteristics that depend on operational and environmental conditions. These proposed preventive maintenance policies are defined and modeled mathematically. The study of these two policies is based on a dynamic system failure law that takes into account the different missions performed. The first step is to determine the optimal business plan to achieve, i.e. the set of missions to perform in order to maximize the profit of missions minus maintenance costs. Thus, for each plan, we determine the maintenance planning considering two policies. The first preventive maintenance policy is periodic and the objective is to determine the optimal number of preventive maintenance to achieve. For the second policy, namely sequential, we calculate the optimal number of preventive maintenance intervals and the duration of these different intervals.     

Optimum block replacement policy over a random time horizon

In this paper we consider the block replacement policy (BRP) for a system operating over a random time horizon. Under such a policy, a system is replaced by a new one either at failure or at a given time interval. The optimality criterion is the expected total replacements cost. Conditions under which an optimal replacement period exits are given. It is shown that BRP over an infinite time horizon is obtained as a particular case of the present work. A numerical example is given to illustrate the proposed replacement model.     

Joint optimization of preventive maintenance and inventory control in a production line using simulation

This paper proposes an integrated method for preventive maintenance and inventory control of a production line, composed of n machines (n?≥?1) without intermediate buffers. The machines are subject to failures and an age-dependent preventive maintenance policy is used. Approximate analytical results are proposed for the one machine case. Simulation software is used to model and simulate the behaviour of the production line of n machines under various maintenance and inventory control strategies. A methodology combining the simulation and genetic algorithms is proposed jointly to optimize maintenance and inventory control policies. Results are compared with the analytical solutions.     

Recovery of Hydroxytyrosol Rich Extract from Two‐Phase Chemlali Olive Pomace by Chemical Treatment

Abstract: A very simple method is proposed to produce hydroxytyrosol, a commercially unavailable compound with well‐known biological properties which justify a potential commercial application. The 2‐phase Chemlali olive pomace is selected as substrate for chemical treatment. Different conditions of chemical treatment, including concentration of acid and alkaline solutions, time and temperature, were assayed. A high amount of hydroxytyrosol (1360 mg/kg of fresh 2‐phase olive pomace) was obtained using water bath after treatment at 80 °C for 90 min with 1 M of H₃PO₄. However, treatment of 2‐phase Chemlali olive pomace using autoclave apparatus could produce a large amount of hydroxytyrosol (1993.60 and 1515.88 mg/kg of fresh alperujo, 1 M acid and basic catalyst, respectively). By taking into consideration practical and economic aspects, acid‐catalyzed treatment was more effective using autoclave conditions, whereas the alkali catalyzed conditions were not very suitable. This study could provide useful information for industry to produce the potentially bioactive compound. Practical Application: The 2‐phase Chemlali olive pomace is selected as substrate for chemical treatment. Treatment of “alperujo” using water bath or autoclave apparatus was carried out. A high amount of hydroxytyrosol was obtained using autoclave apparatus.     

A condition-based maintenance policy for a production system under excessive environmental degradation

In this paper a condition-based maintenance model is proposed for a single-unit system of production of goods and services. The system is subject to random deterioration which impacts not only the product quality but also the environment. We assume that the environment degrades whenever a specific level of system deterioration is reached. The proposed maintenance model aims to assess the degradation in such a way to reduce the deterioration of the environment. To control this deterioration, inspections are performed and after which the system is preventively replaced or left as it is. Preventive replacement occurs whenever the level of the system degradation reaches a specific level threshold. The objective is to determine optimal inspection dates which minimize the average total cost per unit of time in the infinite horizon. Cost function is composed of inspection and maintenance costs in addition to a penalty cost due to environmental deterioration. The maintenance optimization model is formally derived. On the basis of Nelder–Mead method, inspection dates as optimal solutions are computed. A numerical example is provided to illustrate the proposed maintenance model.     

Spatially variant morphological restoration and skeleton representation.

The theory of spatially variant (SV) mathematical morphology is used to extend and analyze two important image processing applications: morphological image restoration and skeleton representation of binary images. For morphological image restoration, we propose the SV alternating sequential filters and SV median filters. We establish the relation of SV median filters to the basic SV morphological operators (i.e., SV erosions and SV dilations). For skeleton representation, we present a general framework for the SV morphological skeleton representation of binary images. We study the properties of the SV morphological skeleton representation and derive conditions for its invertibility. We also develop an algorithm for the implementation of the SV morphological skeleton representation of binary images. The latter algorithm is based on the optimal construction of the SV structuring element mapping designed to minimize the cardinality of the SV morphological skeleton representation. Experimental results show the dramatic improvement in the performance of the SV morphological restoration and SV morphological skeleton representation algorithms in comparison to their translation-invariant counterparts.     

Maintenance strategy for leased equipment

In case of leasing, the user rents equipment for a predetermined time. During this period, all maintenance actions are performed by the lessor. The aim of this research paper consists in determining an optimal maintenance policy for ensuring a minimum reliability, required by the customer. Two strategies are proposed: the first consists in performing preventive actions whenever the system reliability reaches a predefined reliability threshold. These actions are characterized by a reduction of the system age. The objective is therefore to determine the effectiveness factor of the optimal maintenance minimizing maintenance costs. For the second strategy, “improving” actions replace corrective actions during an interval to be determined to minimize maintenance costs. The first strategy will be solved using a numerical procedure and the second strategy uses an algorithm of discrete event simulation.