A renewal process model with failure based PM and imperfect CM for unavailability exploration

PurposeThe paper aims to explore unavailability of dormant systems that are under both preventive and corrective maintenance. Preventive maintenance is considered as a failure based maintenance model, where full renew is realized at the occurrence of every nth failure. It proposes the imperfect corrective maintenance model, where each restoration process deteriorates the system lifetime, probability distribution of which is gradually changed via increasing failure rate.Design/methodology/approachBasic reliability mathematics necessary for unavailability quantification of a system which undergoes a real aging process with maintenance has been derived proceeding from renewal theory. New renewal cycle was defined to cover the real aging process and the expectation of its length was determined. All events resulting in the failure of studied system were explored to determine their probabilities. An integral equation where the unavailability function characterizing studied system is its solution was derived.FindingsPreventive maintenance is closely connected with the occurrence of the nth failure, which starts its renew. The number n can be considered as a parameter which significantly influences the unavailability course. The paper shows that the real aging process characterized by imperfect repairs can significantly increase the unavailability courses in contrast with theoretical aging. This is true for both monitored and dormant systems.Originality/valueAlthough mathematical methods used in this article were inspired and influenced by the work of reference (van der Weide and Pandey, 2015), derivation of final formulas for unavailability quantification considering the new renewal cycle is original. Idea of the real aging process is new as well. This paper fulfils an identified need to manage the maintenance of realistically aging systems.

Design as an Indicator of Tourist Destination Change: The Concept Renewal Cycle at Watkins Glen State Park

For decades, the Tourism Area Life Cycle (TALC) model, its iterations, and its critics have shaped the conversation about change and adaptation at tourist destinations. However, few life cycle models consider the designed landscape as a factor in the evolutionary process or as a signifier of change. This oversight is problematic because the landscape, the aggregation of consciously designed spaces and amenities, is where tourism takes place. It is the physical manifestation of the tourist destination and therefore significantly influences how the site is organized, consumed, and evaluated. To illustrate the landscape’s importance, this article proposes a new life cycle model called the Concept Renewal Cycle (CRC), which tracks the intent of the designed landscape, the concept, to understand and document destination change. The model introduces and utilizes relevancy as the variable that determines concept success and instigates action. The proposed model and other prominent life cycle models are analyzed and compared through the case study of Watkins Glen State Park in New York state. While the other models struggle to reflect the evolution at Watkins Glen, the CRC shows resilience by eschewing TALC’s inevitable, time-based decline structure in favor of a cyclical pattern where concept revision allows for prolonged maturity.

Replacement Policy for Cold Standby Repairable System with Priority in Use by Using Arithmetico-Geometric Process

In this paper, we consider the arithmetico-geometric process (AGP) repair model. Here, the system has two nonidentical component cold standby repairable system with one repairman. Under this study, component 1 has given priority in use. It is assumed that component 2 after repair is as good as new, whereas the component 1 follows AGP. Under these assumptions, by using AGP repair model, we present a replacement policy based on number of failures, [Formula: see text], of component 1 such that long-run expected reward per unit time is maximized. For this policy, system can be replaced when number of failure of the component 1 reaches to [Formula: see text]. Working time of the component 1 is AGP and it is stochastically decreasing whereas repair time of the component 1 is AGP which is stochastically increasing. The expression for long-run expected reward per unit time for a renewal cycle is derived and illustrated proposed policy with numerical examples by assuming Weibull distributed working time and repair time of the component 1. Also, proposed AGP repair model is compared with the geometric process repair model.

2nd Geomagnetic Information Renewal Cycle in the Republic of Croatia – First Results

The 2nd Geomagnetic Information Renewal Cycle started in 2017, pursuant to a request from the State Geodetic Administration and Ministry of Defence to ensure actual declination and its annual variation across the territory of Republic of Croatia. A test survey was performed at POKUpsko as part of the project in 2017. The PRM1 Primary Repeat Station had been destroyed, and the survey performed at a secondary location established in 2011, which subsequently became the primary location, known as PRM2. In this paper, the results of 2017 measurements reductions are presented, along with reductions in PRM1 and PRM2 measurements in 2011, and differences between the PRM1 and PRM2 locations, which are necessary to maintain the continuity of measurements at Pokupsko.

Asset management system for business management of water suppliers

Many water suppliers in Japan are required to renew aged waterworks facilities systematically in spite of the decline in revenues due to the decrease in the population. Moreover, they are needed to build waterworks facilities with high earthquake resistance. Therefore, it is necessary for water suppliers to manage waterworks effectively and efficiently in order to build sustainable waterworks. In this paper, to support sound business management, a method of water asset management is arranged systematically. And also an actual example with this systematic method in a water supplier is introduced in which reduction of renewal costs by optimization of ability of the waterworks facilities and setting renewal cycle standards is explained. Furthermore, a perspective of renewal costs taking into account the acceleration of earthquake-resistance strengthening plan and equalization of renewal demands is shown.

Dynamics of pre- and post-choice behaviour: rats approximate optimal strategy in a discrete-trial decision task

We simulate two types of environments to investigate how closely rats approximate optimal foraging. Rats initiated a trial where they chose between two spouts for sucrose, which was delivered at distinct probabilities. The discrete trial procedure used allowed us to observe the relationship between choice proportions, response latencies and obtained rewards. Our results show that rats approximate the optimal strategy across a range of environments that differ in the average probability of reward as well as the dynamics of the depletion-renewal cycle. We found that the constituent components of a single choice differentially reflect environmental contingencies. Post-choice behaviour, measured as the duration of time rats spent licking at the spouts on unrewarded trials, was the most sensitive index of environmental variables, adjusting most rapidly to changes in the environment. These findings have implications for the role of confidence in choice outcomes for guiding future choices.

AN IMPERFECT PROCESS POLICY WITH PRODUCTION CORRECTION AND REORGANIZATION

This study applies imperfect production processes to obtain in-control state by production correction and reorganization. Production processes are classified into two types of state: one is the type I state (out-of-control state) and the other is the type II state (in-control state). The type I state involves adjustment of the production mechanism. Production correction is either imperfect; worsening a production system, or perfect, returning it to "in-control" conditions. After N type I states, the operating system must be reorganized and returned to the beginning condition. At the beginning of the production of the each renewal cycle, the state of the process is not always to be restored to "in-control". The mean loss cost until "in-control" state, is determined. The existence of a unique and finite optimal N for an imperfect process under certain reasonable conditions is shown. A numerical example is presented.