Reliability Importance Measures considering Performance and Costs of Mechanical Hydraulic System for Hydraulic Excavators

Although some reliability importance measures and maintenance policies for mechanical products exist in literature, they are rarely investigated with reference to weakest component identification in the design stage and preventive maintenance interval during the life cycle. This paper is mainly study reliability importance measures considering performance and costs (RIMPC) of maintenance and downtime of the mechanical hydraulic system (MHS) for hydraulic excavators (HE) with energy regeneration and recovery system (ERRS) and suggests the scheduled maintenance interval for key components and the system itself based on the reliability R i t . In the research, the required failure data for reliability analysis is collected from maintenance crews and users over three years of a certain type of hydraulic excavators. Minitab is used for probable distribution estimation of the mechanical hydraulic system failure times, and the model is verified to obey Weibull distribution. RIMPC is calculated by multiplying the reliability R i t and weighting factor W i and then compared with other classical importance measures. The purpose of this paper is to identify the weakest component for MHS in the design stage and to make appropriate maintenance strategies which help to maintain a high reliability level for MHS. The proposed method also provides the scientific maintenance suggestion for improving the MHS reliability of the HE reasonably, which is efficient, profitable, and organized.

Optimising the Preventive Maintenance Interval Using a Semi-Markov Process, Z-Transform, and Finite Planning Horizon

This chapter uses a semi-Markov process and the z transform to find the optimal preventive maintenance interval when dealing with maintenance decision making for a finite time planning horizon. The result is a method that can be easily implemented to assets for which a Weibull reliability analysis exists. The suggested preventive interval formulation is simple and practical. The requirements to apply this simple formula are related to the existence of asset´s reliability data as well as cost/rewards that the assets have when remaining or transitioning to a given state. The application of this method can be very straightforward, and the tool can become a good decision support tool allowing “what if” analysis for different time horizon and maintenance policies.

A Study on PF–IFF-Based Diagnosis Model of Plant Equipment Failure

There are two types of maintenance policies for equipment: breakdown maintenance and preventive maintenance. In the case of applying preventive maintenance, the maintenance is carried out based on time or the condition of the equipment. However, with the development of Information and Communications Technologies (ICT) and the Internet of Things (IoT) technology, the data collected from equipment has rapidly increased and the use of Condition-Based Maintenance (CBM) to perform appropriate maintenance based on the condition of the equipment is increasing. In this study, based on gathered sensor data, we introduce an approach to diagnosing the condition of the equipment by extracting specific data features related to the types of failures that occur with equipment. To this end, we used the K-means clustering method, support vector machine (SVM) classifier, and Pattern Frequency–Inverse Failure mode Frequency (PF–IFF) method with the Term Frequency–Inverse Document Frequency (TF–IDF) method. As a case study, we applied the proposed approach to a centrifugal pump and carried out computational experiments for assessing the performance and validity of the proposed approach.

The Damage Control of Liquid Waste Pumping Machines in Palm Oil Companies

X is a company that works in the field of oil palm plantations and has a palm oil production capacity of 60 tons per hour. The products of palm oil that have been produced are Crude Palm Oil (CPO) and Palm Kernel Oil (PKO). The various kinds of waste produced by the company as a result of the palm oil industry process are liquid waste, palm kernels, fiber and seed shells. Liquid waste is used as organic fertilizer for oil palm plantations which will be sent through a liquid waste pump machine. Damage that occurs to the liquid waste pump machine will inhibit the delivery of liquid waste to the plantation, thus affecting the yield of palm oil from the plantation itself. This study describes the application of repair and preventive maintenance policies for liquid waste pump machines by looking at the frequency of damage to the liquid waste pump engine and predicting the delivery of liquid waste to the pump engine for the next period as well as providing solutions for handling damage that occurs in the liquid waste pump engine. From the results of calculations on data processing, the results of how to control the causes of damage that occur in the liquid waste pump machine can be overcome by using the Preventive Maintenance Method within a period of 1 month and maintenance of every component in the liquid waste pump machine within 1 cycle, namely 357.27 hours with a repair time of 5.82 hours. Controlling other causes of damage is to add a filter to the liquid waste pool so that stones, leaves and liquid waste husks do not hinder the suction pipe of the liquid waste pump machine.

Optimizations of Managerial Maintenance Policies

This paper takes up managerial maintenance policies during different phases for mission executions. When a mission execution is divided into two phases and three phases respectively, replacement, minimal repair and keeping failure status become alternatives for managerial maintenance policies. Further, we give approximations of the above managerial maintenance policies to make the computations simple. In this paper, keeping failure status is considered as the last choice for the last phase of mission executions. We aim to minimize the expected maintenance costs for the total mission executions. All of the discussions are made analytically and their numerical examples are given.

Optimisation of maintenance in delivery systems for cytostatic medicines

Background The real-world application of maintenance in organisations brings together a number of maintenance policies in order to achieve the desired availability, efficiency and profitability. However, the literature mostly chooses a single maintenance policy, and so the decision process is not suited to the real conditions in the company to which it is applied. Our study takes a combination of maintenance policies as alternatives, and so conforms to the actual practice of maintenance in organisations. Furthermore, it introduces the possibility of including extra spare parts, or outsourcing maintenance policies. Although the selection of maintenance policies has been applied to many kinds of business and of machine, there is almost no instance of its application to hospitals, and it has never been applied to delivery systems for cytostatic drugs. Methods The model uses the fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), which is recognised as being highly suitable for solving group decision-making problems in a fuzzy environment. Fuzzy set theory is also considered to be more proficient than crisp numbers for handling the ambiguity, imprecisions, data scarcity, and uncertainty inherent in decisions made by human beings. The judgements required were obtained from a decision group comprising the heads of facilities maintenance, maintenance of medical equipment, health and safety at work, environment, and programming-admission. The group also included care staff; specifically, the heads of the main clinical services, and the medical supervisors. The model includes original criteria, such as Quality of health care, which measures impact on care as a function of mean availability of each alternative. It also considers Impact on hospital management via the criteria: Working environment in the organisation and Impact on health care; the former criterion measures equality among care services in the hospital, while the latter assesses the effect on regional health cover. The model was built using real data obtained from a state hospital in Spain. The model can also be easily applied to other national and international healthcare organisations, providing weights specific to the criteria. These are produced by a decision group from each healthcare organisation and the alternatives are updated in accordance with what is considered important in each hospital. Results The results obtained from the model recommend changing the alternative that is currently in use, Corrective and Preventive Maintenance, to Corrective and Preventive Maintenance plus two spare hoods. This alternative would lead to an availability of 1 (the highest possible) in the systems for preparing personalised cytotoxic drugs, and so the quality of service is therefore very high. Additionally, it could offer services to all the users of the hospital, and also offer cover in the preparation of cytotoxic medicines to other hospitals in the catchment area. Conclusions The results suggest the possibility that improvements to the support and logistical systems, which include maintenance, traditionally held to have no effect on quality of care, may be key to improving care quality, but also in reducing risk to patients, care and non-care staff, and the environment.

The post-warranty random maintenance policies for the product with random working cycles

Advanced sensors and measuring technologies make it possible to monitor the product working cycle. This means the manufacturer’s warranty to ensure reliability performance can be designed by monitoring the product working cycle and the consumer’s post-warranty maintenance to sustain the post-warranty reliability can be modeled by tracking the product working cycle. However, the related works appear seldom in existing literature. In this article, we incorporate random working cycle into warranty and propose a novel warranty ensuring reliability performance of the product with random working cycles. By extending the proposed warranty to the post-warranty maintenance, besides we investigate the postwarranty random maintenance policies sustaining the post-warranty reliability, i.e., replacement last (first) with preventive maintenance (PM). The cost rate is constructed for each post-warranty random maintenance policy. Finally, sensitivity of proposed warranty and investigated polices is analyzed. We discover that replacement last (first) with PM is superior to replacement last (first).