Phuc Do

University of Lorraine | UdL · CRAN - Centre de Recherche en Automatique de Nancy

This paper proposes a novel anomaly detection methodology for industrial systems based on Digital Twin (DT) ecosystems. In addition to DTs, conceived as a digital representation of a physical entity, this paper proposes a new concept of DT focused on modeling connections between physical behaviors. This new DT concept is called Snitch Digital Twin...

The objective of this paper is to study the effectiveness of an opportunistic condition-based maintenance strategy for the sea water pumps in a nuclear power plant. For the presented study a primary seawater system consisting of four sea water pumps, supplied by three water intake chambers, have been considered. There exists functional dependency a...

We present a novel framework for diagnostics and prognostics for multi-component systems with wear interaction between components. The principal elements of this framework are: health-state indicator extraction using signal-processing; clustering of wear phases using a Gaussian mixture model; a stochastic multivariate wear model; and prediction of...

Currently, in manufacturing, massive useful data about health condition and maintenance is often available thanks to Industry 4.0 technologies. However, how to take advantage of historical data to optimize maintenance policies for multi-component systems has still been a challenging problem. This is especially true when maintenance cost models at c...

Maintenance planning for complex systems has still been a challenging problem. Firstly, integrating multiple dependency types into maintenance models makes them more realistic, however, more complicated to solve and analyze. Secondly, the number of maintenance decision variables needed to be optimized increases rapidly in the number of components,...

It is well-known that maintenance decision optimization for multi-component systems faces the curse of dimensionality. Specifically, the number of decision variables needed to be optimized grows exponentially in the number of components causing computational expensive for optimization algorithms. To address this issue, we customize a multi-agent de...

Anticipating system failures using predictive strategies based on efficient prognostics has become an important topic in manufacturing where maintenance plays a crucial role. As such, promising prognostics approaches use data-driven machine learning techniques, though the initial data set for learning is often small as failure occurrences are rare....

This paper describes the development of a decision support system (DSS) for evaluating membrane restoration strategy. The engine of the DSS is a digital twin (DT), a virtual representation of wear (degradation) and restoration of membrane elements in a reverse osmosis (RO) pressure vessel. The basis of the DT is a mathematical model that describes...

Light-emitting diodes (LEDs) are a solid-state light source being used in numerous applications, including display, communications, medical services, etc. However, the reliability assessment of LED components is still challenging due to the growing up of the LED complexity and/or the miniaturization of assembly technologies. To face this challenge,...

This chapter provides some contributions for opportunistic maintenance optimization of multi-component system in the arising context of on-line monitoring and strong interactions between components. The key point is, on one hand, to model and integrate different kinds of dependencies (stochastic dependence, structural dependence and economic depend...

Prognostics and health management can be described as an emerging engineering discipline which studies and associates the degradation processes to system lifecycle management. It allows for system health state assessment in real-time, as well as predicting its future health states. In this chapter we present a methodology that leads towards PHM of...

For maintenance optimization of multi-component systems, opportunistic maintenance has been addressed in many studies since it allows considering the advantages of dependences between components in maintenance decision-making process. In the literature, economic dependence, which implies that joint maintenance of several components can reduce the m...

Importance measures have been widely used as meaningful decision-aiding indicators in reliability engineering, risk management and maintenance optimization. However, few importance measures integrates the actual condition (working states or degradation levels) of components that dynamically evolves with time. This work develops a novel time-depende...

With the popularization of big data, an increasing number of discrete event data have been collected and recorded during system operations. These events are usually stored in the form of event logs, which contain rich information of system operations and have potential applications in fault diagnosis and failure prediction. In manufacturing process...

In this paper, we develop a maintenance model for systems subjected to multiple correlated degradation processes, where a multivariate stochastic process is used to model the degradation processes, and the covariance matrix is employed to describe the interactions among the processes. The system is considered failed when any of its degradation feat...

Maintenance plays a key role in controlling manufacturing systems within normal operations. Consistent control within production requirements is difficult due to the complexity of manufacturing systems; that is, many components that are economically and structurally interdependent. Structural dependence between components implies that maintenance r...

Structural dependence between components within industrial architecture implies that components structurally form a connected set (a block), and the maintenance of a component requires disassembly of some other components in order to reach it. In that way, the disassembly operations for maintenance may have a significant impact on the degradation p...

Opportunistic maintenance (OM) is a key solution to reduce the maintenance costs or/and to improve the system dependability/performance. However, the existing OM models are mainly developed to specific classes of systems (series structures) with specific types of maintenance opportunities (MOs) such as component failure. The objective of this paper...

In recent years, thanks to the rapid advances in technology, the optoelectronic devices become more and more complex with strong interactions (e.g. multi-chip module, chip-on-chip integration, photonic integrated circuit, etc) and require high performance levels. One of the most recognized challenges of such a system is its reliability assessment....

This paper proposes a condition-based maintenance (CBM) policy for a deteriorating system whose state is monitored by a degraded sensor. In the literature of CBM, it is commonly assumed that inspection of system state is perfect or subject to measurement error. The health condition of the sensor, which is dedicated to inspect the system state, is c...

This paper presents a dynamic grouping and routing approach for the maintenance optimization of a geographically dispersed production system (GDPS) consisting of several production sites located far apart from each other. Only one maintenance center is in charge of the preventive maintenance of the system. Maintenance grouping and routing are two i...

The quality of condition monitoring is an important factor affecting the effectiveness of a condition-based maintenance program. It depends closely on implemented inspection and instrument technologies, and eventually on investment costs, i.e., a more accurate condition monitoring information requires a more sophisticated inspection, hence a higher...

This paper develops a model of a condition-based maintenance policy for a two-component system with both stochastic and economic dependencies. The stochastic dependency is such that the degradation rate of each component depends not only on its own state (degradation level) but also on the state of the other component. The economic dependency is su...

Condition-based maintenance has been developed and successfully applied in various industrial systems to preventively maintain the correct equipment at the right time with regard to its current health “condition” such as oil temperature, harmonics data, and vibration. The monitoring of these conventional indicators may however be costly. Moreover,...

The degradation process of complex multi-component systems is highly stochastic in nature. A major side effect of this complexity is that components of such systems may have unexpected reduced life and faults and failures that decrease the reliability of multi-component systems in industrial environments. In this work, we provide maintenance practi...

In the framework of maintenance optimization of multicomponent systems, dynamic grouping maintenance based on rolling horizon has developed and became an interesting approach. However, most existing dynamic grouping models assume that the maintenance duration is negligible. This assumption may be not always relevant and limits the application of th...

This chapter provides some contributions for maintenance optimization of multicomponent system in the arising context of on-line monitoring and dynamic decision-making under specific constraints. The key point is, on one hand, to develop maintenance models taking into account economic dependence and some maintenance constraints. On the other hand,...

The paper presents a study on health diagnosis and prognosis of an industrial diesel motor. Two well-known approaches, Hidden Markov Model (HMM) and particle filter (PF), are applied from real recorded data with different measurements. The recorded data is firstly pre-processed and health indicator is then chosen before implementing each used appro...

Maintenance and inventory optimizations are two interrelated processes but often investigated separately in the literature. Joint optimization of these processes can reduce the total maintenance and inventory cost, it may however lead to a complex problem with a large numbers of decision parameters to be optimized. To face this open issue, in this...

This paper proposes a general deterioration model for a multi-component system. The deterioration process of a component depends upon the operational conditions, the component’s own state, and also the state of other components. An experimental platform that aims to provide more insight into the true nature of degradation of multi-component systems...

Condition-based maintenance (CBM) has been introduced in industrial systems to maintain preventively the correct equipment at the right time with regards to its current health “condition” represented mainly the conventional indicators such as oil temperature, harmonics data, vibration, etc. The monitoring of these indicators is done through sensors...

Nowadays, industrial enterprises are facing up to new challenges to well optimize their performances, with regards not only to conventional performances (e.g. reliability or productivity) but also to emerging ones as those related to sustainability issues. Indeed, sustainability indicators have to be considered now in the decision-making process of...

The paper presents firstly an overview of various definitions/concepts of energy efficiency and their related applications in different contexts, especially in industrial sectors. Each definition/concept is analyzed and recommended for different decision-making levels. Then a multi-level approach is described in detail for evaluating energy efficie...

Manufacturing systems operate under high production, reliability and safety requirements due to the complicated technology involved and hazardous consequences for product/process in case of failures. In that way,Maintenance plays a key role to sustain the system within its nominal operation space. It consists in implementing strategies to control o...

In this paper, a novel predictive maintenance policy with multi-level decision-making is proposed for multi-component system with complex structure. The main idea is to propose a decision-making process considered on two levels: system level and component one. The goal of the decision rules at the system level is to address if preventive maintenanc...

Industrial plants are facing today with new challenges to well optimize performance of their operation and maintenance. For example, the sustainability paradigm is introducing new requirements to be taken into account in the decision-making process. In that way, energy consumption (EC) and energy efficiency (EE) are two critical performances impact...

The paper deals with a condition-based maintenance policy for a two-component system with dependencies. Two kinds of dependency are investigated. The first is state dependence whereby the deterioration speed of each component depends not only on its own state (deterioration level) but also on the state of the other. The second is economic dependenc...

In this paper, a novel predictive maintenance policy with multi-level decision-making is proposed for multi-component system with complex structure. The main idea is to propose a decision-making process considered on two levels: system level and component one. The goal of the decision rules at the system level is to address if preventive maintenanc...

This paper presents a stationary grouping maintenance strategy for multi-component systems whose structure could be a mixture of the basic structures such as series structures, parallel structures, k -out-of n , etc. The proposed preventive maintenance decision-making rules are based on the joint consideration of the mean remaining lifetime (MRL),...

The paper deals with a maintenance grouping approach for multi-component systems whose components are connected in series. The considered systems are required to serve a sequence of missions with limited breaks/stoppage durations while maintenance teams (repairmen) are limited and may vary over time. The optimization of the maintenance grouping dec...

The present work deals with a dynamic grouping maintenance strategy for complex systems whose structure may lead to both positive and negative economic dependencies. Impacts of the system structure and preventive maintenance durations on maintenance grouping are investigated. To find the grouped maintenance plan, a dynamic maintenance approach base...

This paper presents a predictive condition-based maintenance strategy for multi-component systems whose structure may impact components deterioration process. To select components for preventive maintenance actions, a decision rule relying on both structural importance measure of components and their predictive reliability that can be estimated at...

Telecommunication industry is predicted to have an important role in total energy consumption of industry area. Thus, the increasing energy cost in operational costs demands effective tools to identify energy efficiency indicators (EEIs) and predict the evolution of energy efficiency performance (EEP). The energy efficiency (EE) improvement of any...

This paper deals with a proactive condition-based maintenance (CBM) considering both perfect and imperfect maintenance actions for a deteriorating system. Perfect maintenance actions restore completely the system to the ‘as good as new’ state. Their related cost are however often high. The first objective of the paper is to investigate the impacts...

The paper deals with a modified time based maintenance policy for mono-unit systems with the presence of emergency spare part ordering cost due to unplanned maintenance actions. Comparing with existing maintenance policies in the literature, in the proposed one an unplanned replacement threshold is in addition introduced to balance the emergency or...

The paper presents firstly an overview of various definitions/concepts of energy efficiency and their related applications in different contexts, especially in industrial sectors. Each definition/concept is analyzed and recommended for different decision-making levels. Then a multi-level approach is described in detail for evaluating energy efficie...

The paper presents a joint predictive maintenance and spare parts provisioning policy for gradually deteriorating multi-component systems with complex structure. The decision-making process related to maintenance, spare parts ordering, as well as inspections scheduling is based on both RUL prediction and structural importance measure. Moreover, eco...

This paper presents firstly a dynamic grouping maintenance strategy for multi-component systems with positive economic dependence, which implies that combining maintenance activities is cheaper than performing maintenance on components separately. Preventive maintenance durations and multiple occurrences of maintenance activities within scheduling...

This paper deals with a predictive maintenance strategy for multi-component systems whose structure may impact the evolution of components' deterioration that can be inspected at regular intervals of time. A decision rule relied on both structural importance of components and their predictive reliability is proposed to select components to be preve...

Nowadays, industrial systems are more and more larger with many components which are connected in a complex structure. The systems usually ask for a high investment cost (expensive components) and many preparation tasks for maintenance. With these system, a maintenance policy should take into account the complexity of system structures and give pri...

The aim of this study is to propose a predictive grouping maintenance strategy for complex structure systems with gradually deteriorating units. The unit's conditions are inspected at regular time intervals. Preventive maintenance decision rule is mainly based on the group improvement importance measure defined as a ratio of the improvement ability...

This paper deals with a proactive condition-based maintenance (CBM) considering both perfect and imperfect maintenance actions for deteriorating systems. Perfect maintenance actions restore completely the system to the 'as good as new' state. Their related cost are however often high. Imperfect preventive maintenance restores partially the system w...

This paper presents a dynamic grouping maintenance strategy for complex systems whose structure may lead to both positive and negative economic dependencies. Preventive maintenance (PM) durations are investigated and considered in the proposed maintenance model. Thanks to the rolling horizon spirit, the maintenance planning can be updated to take i...

This paper deals with a remaining useful life (RUL) based maintenance policy for single unit deteriorating systems whose condition are periodically monitored. Thank to the RUL information, which is estimated from the available monitoring information, various decisions related to inspections, logistic support, maintenance opportunities and maintenan...

This paper presents a condition-based maintenance policy considering aspects of maintenance cost and productivity for a single-unit deteriorating production system whose condition is periodically monitored. Imperfect preventive maintenance actions, which restore the production system to better than old, are considered with both deterministic and ra...

This paper deals with a condition-based maintenance (CBM) model considering both perfect and imperfect maintenance actions for a deteriorating system whose condition is aperiod-ically monitored according to a remaining useful life (RUL) based-inspection policy. Perfect maintenance actions restore completely the system to the 'as good as new' state....

This paper deals with a condition-based maintenance (CBM) model considering both perfect and imperfect maintenance actions for a deteriorating system whose condition is aperiod- ically monitored according to a remaining useful life (RUL) based-inspection policy. Perfect maintenance actions restore completely the system to the ’as good as new’ state...

The paper deals with a development of the rolling horizon approach introduced recently for grouping maintenance strategies of multi-component systems by integrating two efficient optimization algorithms. The proposed approach can help to construct an optimal maintenance planning with a given availability constraint under limited repairmen. Thanks t...

This paper presents a dynamic grouping maintenance strategy for complex systems whose structure may lead to both positive and negative economic dependence which imply that combining maintenance activities is cheaper (or more expensive respectively) than performing maintenance on components separately. Binary Particle Swarm Optimization (BPSO) algor...