A method for detecting possible near miss ship collisions from AIS data

The study of supply chain resilience (SCRES) continues to gain interest in the academic and practitioner communities. The purpose of this paper is to present a focused review of the SCRES literature by investigating supply chain (SC) capabilities, their relationship to SCRES outcomes and the underpinning theoretical mechanisms of this relationship.,The paper uses the systematic literature review approach to examine 383 articles published between 2000 and 2017, ultimately down selecting to the most relevant 228 peer-reviewed studies. Context-interventions-mechanisms-outcomes (CIMO) logic is applied to organize and synthesize these peer-reviewed studies. A typological framework is developed from the CIMO-based classification of the SCRES literature.,The findings of this study outline the gaps in the SCRES literature and present an agenda for future research.,This paper presents an exploratory research; therefore, the typological model presented is just one of the possible perspectives.,The typology of SCRES literature can help practitioners to understand SCRES and to measure and assess the resilience of SCs.,The paper provides clear definitions of SCRES constructs, develops a typological framework to further understand SCRES and identifies SCRES measures and assessment techniques.

Supply chain resilience: a systematic literature review and typological framework

Condition based maintenance (CBM) uses the operating condition of a component to predict a failure event. Compared to age based replacement (ABR), CBM usually results in higher availability and lower maintenance costs, since it tries to prevent unplanned downtime and avoid unnecessary preventive maintenance activities for a component. However, the superiority of CBM remains unclear in multi‐component systems, in which opportunistic maintenance strategies can be applied. Opportunistic maintenance aims to group maintenance activities of two or more components in order to reduce maintenance costs. In a serial system, this may also result in less downtime of the production line. The aim of this paper is to examine the impact of opportunistic maintenance on the effectiveness of CBM. We simulate a small system consisting of three components in series and vary the number of components under a CBM policy, the length of the opportunistic maintenance zone, the cost benefits of grouping maintenance activities, and t...

Condition based maintenance in the context of opportunistic maintenance

Real-time prediction of remaining useful life and preventive opportunistic maintenance strategy for multi-component systems considering stochastic dependence

Joint optimization of condition-based opportunistic maintenance and spare parts provisioning policy in multiunit systems

We present an overview of some recent developments in the area of mathematical modeling of maintenance decisions for multi-unit systems. The emphasis is on three main groups of multicomponent maintenance optimization models: the block replacement models, group maintenance models, and opportunistic maintenance models. Moreover, an example of a two-unit system maintenance process is provided in order to compare various maintenance policies.

On problems of multicomponent system maintenance modelling

Safety and Reliability: Methodology and Applications

The paper considers problem of city transportation system performance. Reliability analysis of such a complex system is complicated by several factors. One of th em is the possibility of logistic support elements unreliability defined as unavailability of spare elements when de sired, what in result may lead to decrease of perfo rmance of the system being supported. Thus, both systems must be considered in a single model. However, the simultaneous setting of all structural parameters ( .g. redundancy, repair shop capacity) and control variables (e.g. spare part inventory levels, maintenance poli cy parameters, time resource) is mathematically a h ard problem. This paper investigates Petri net model of the system with the use of Monte Carlo simulation as a solution technique. Comparison of the simulation re sults with characteristics of real-life system is g iven. Kowalski Marcin, Magott Jan, Nowakowski Tomasz, Wer bińska-Wojciechowska Sylwia Analysis of transportation system with the use of P etri nets 266 maintenance parameters (or cost of maintenance) on one side, and the performance level on the other. The interest in development and investigation of maintenance problems has been extensively discussed in the literature since the early 1960s. The basic review in the area of maintenance modelling i s prepared by Pierskalla & Voelker [20], where authors investigated discrete time vs. continuous time maintenance models, later updated by ValdezFlores & Feldman [22]. For other surveys see e.g. [3], [14], [15], [1], [19], [21], [23], [24]. However, most of the maintenance models investigated in the literature on reliability theor y assume, that all the necessary logistic support resources, which include maintenance resources, support personnel, logistic information and data, spares and repair parts, and facilities, are immediately provided when it is desired. In practic e, the repair capacity is not infinite, and logistic information may be unreliable. Moreover, the influence of a spare provisioning policy on the maintenance policy also cannot be ignored, since spares are ordered and carried in the limited quantity, and the procurement lead time is not negligible. The problem of providing an adequate and efficient supply of spare parts, in support of maintenance an d repair of operational systems, has been researched for many decades. Recent overview of these models is made by Nowakowski & Werbi ńskaWojciechowska in [17]. Consequently, reliability of complex systems (e.g. transportation systems, aircraft systems) can be difficult to analyze for several reasons. First, bo th systems, logistic and being supported are integrate d and thus should be considered in a single model. However, growing body of existing literature in the investigated research area treats maintenance, replacement and inventory decisions separately [24] . Second, commonly used analytical techniques for reliability evaluation are applied probability theo ry, renewal reward processes, Markov decision theory, and Fault Trees. Each of these techniques has advantages and disadvantages and the choice depends on the system being modelled. All of them require simplifying assumptions about time to failure behaviour of the system components. Moreover, Markov method analyses the system by identifying all the different states in which the system can reside and is able to produce accurate system reliability measures by assigning rates of transition between these states. However, the Markov method has its own drawbacks in its application for a relatively large system to establ ish the state transition model is an intractable task. Traditional Fault Tree Analysis (FTA) [6] is probabilistic approach to safety, reliability, and risk analysis. Traditional fault trees contain Boolean gates to represent how component failures combine to produce system failures. These fault trees are n ow called static. In papers [4], [5], dynamic fault tr ees (DFTs) are presented. Gates of DFTs can express the following features: • dynamic replacement of failed components from pools of spares, • failures can occur only in a predefined order. In paper [2], DFTs have been extended by repair boxes. These boxes can express a repair time of components. In this paper, transformations of different gates and repair boxes into Stochastic Hi gh Level Colored Petri Net are given. In calculation of probabilistic characteristics of systems using DFTs, the following formalisms are used: Markov models [4], [5], Petri nets [2], Bayesian networks [13]. When analyzing the transportation system, we have to analyze not only repair and lead time, but time consuming replacement process and time resource as well. Hence, DFTs with repair boxes are not sufficient to represent the transportation system. Moreover, Fault Tree with Time Dependencies provides an interesting solution for nondeterministic models [11], [12]. In these models, time parameters are described by minimal and maximal values, but without probabilistic characteristics. The FTTD technique has been proposed as a convenient approach to describe the values of the delay times of system of systems task performance on the ESREL conference in 2008 [10]. The investigated problem has regarded to simple logistic support model performance. Later, there is proposed method application example presented in [9]. However, this method cannot be applied when time between failures and repair times are expresse d probabilistically. In contrast to the analytic approaches Monte Carlo simulation can be broadly used. However, Monte Carlo simulation is time-consuming because of the intensive computations. This is because an extremely large number of simulated samples may be needed to estimate the reliability parameters at a high level of confidence. Following this consideration, in the paper, Petri n ets are used to support the reliability analysis of complex real-life system performance. The primary contribution of this research is to propose a Stochastic High-level Petri Net model for presented below transportation system. This model is based on standard of High-level Petri Net [7] an d on generalized stochastic Petri nets [1]. For this model, simulation experiments have been

Analysis of transportation system with the use of Petri nets

Combined transportation system reliability model is presented. The model contains 5 operation and maintenance states. The model is built using phased-mission model that describes the changes of transportation means. Reliability of CT as analysed using Markov theory. Some examples of the model sensitivity on the rate of rail phase are shown.

Tomasz Nowakowski

Papers

On problems of multicomponent system maintenance modelling

Safety and Reliability: Methodology and Applications

Analysis of transportation system with the use of Petri nets

Reliability Model of Combined Transportation System

Metodyka prognozowania niezawodności obiektów mechanicznych