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In this article, we present the results of a study examining the behavior of various inventory stocking methodologies in repair/rework operations. A major area of focus is on the sensitivity of key model parameters to stochastic replenishment lead times, product demand, and overhaul factors. A case study in a US Army depot provides validation for the effort. Simulation results indicate the current depot stocking methodologies are adequate in ideal conditions, but are less effective in more challenging and realistic scenarios. Results also indicate that some commonly used inventory models are quite robust to stochastic operating parameters in the unique/rework environment.

The feasibility and desirability of reverse logistics in market-motivated contexts are examined in China. Interactions between the major barriers, that hinder or prevent the application of reverse logistics in China are analyzed. Management’s key task is to diagnose barriers to the application of reverse logistics that could be crucial to the organization’s future survival. Simultaneity, a value delivery system exists to create value for customers and environments by supplying needed products and services. Value delivery systems are at the heart of every firm and, more than anything else, determine that, whether the firm survives in the marketplace or disappears into bankruptcy or takeover. The processes and model of market-motivated reverse logistics value delivery system are discussed, and the processes content and model are presented. Simultaneity, based on the advantage of the Third Party Reverse Logistics Providers (3PRLs) and Outsourced Service Providers, an integrated evaluation model is built to select 3PRLs by using the integrated decision-making methods. Reflecting the comprehensive information requirement, the Analytic Hierarchy Process and entropy approaches are applied to calculate the objective weights. A new kind of relative similarity degree is established by combining the Euclidean distance with the grey correlation degree. An example demonstrates the model’s efficiency.

The powerful forces that are transforming healthcare can generate enormous economic potential for those who are able to employ effective survival techniques in the short term and at the same time plan for success in the long term. To accomplish this, an organization must harness the forces driving transformation and use them to its advantage. Despite the best efforts of senior healthcare executives, major change initiatives often fail. Change threatens the very stability and continuity that managers are attempting to control; therefore change and managers are not natural partners. Even managers aware of the need to change resist the parts that appear too major, too risky, or too “different”. This understanding of change, transformation and reinvention are crucial for all health‐care organizations moving forward at turbulent speeds. Change has its problems and successes are not abundant. This article will examine change strategies; their failures and successes; the role of the leader in this process; overcoming barriers and resistance, key steps to succeed in change efforts and, finally, alternative strategies to build the change process.

The purpose of this article is to present a new split system model (SSM) that predicts the reliability of complex systems with multiple preventive maintenance (PM) actions in the long term.

The SSM was developed using probability theory based on the concept of separating repaired and unrepaired components within a system virtually when modelling the reliability of the system after repairs. After theoretical analysis, a case study and Monte Carlo simulation were used to evaluate the effectiveness of the newly developed model.

The model can be used to determine the remaining life of systems, to show the changes in reliability with PM actions, and to quantify PM intervals after imperfect repairs.

SSM can be used to predict the reliability of complex systems with multiple PM actions, and hence can be used to support asset PM decision making over the whole life of the asset, such as scheduled PM times and spare parts requirements. An asset often has some vulnerable components, i.e. where the lives of these components are much shorter than the rest of the asset. In this case, PM is often conducted on these vulnerable components for maximising the useful life of the asset. The specific formulae derived in this paper can be used to predict the reliability of the asset for this scenario.

The proposed model uses a new concept of split systems to predict the changes of reliability of complex systems with multiple PM actions. Asset managers will find this model to be a useful tool in the optimisation of their asset PM strategies.

To provide a unified analytical tool for the theoretical and practical analysis of four‐phase systems under sinusoidal condition but also under dynamic condition and to understand the contribution of each sequence components on the energy and air gap field points of view.

Starting from the general procedures of analysis for the n‐phase symmetric systems, the analysis of four‐phase system is first developed in the phasorial domain, then, with reference to the asymmetrical sinusoidal conditions in terms of symmetric components. As a complement to what is already present in the literature, finally a formalization of the four‐phase systems in an instantaneous form based on the Lyon and Clarke‐Park vectors is proposed. Furthermore, a particular emphasis will be given to the physical meaning of the involved quantities, to their link with the three‐phase quantities and to the instantaneous energetic interpretation.

Four phase system presents the existence of the pseudozero‐sequence component which is an additional descriptive variable of the four‐phase configuration, absent in the three‐phase system. Pseudozero‐sequence component results completely independent on the need for a neutral wire. Knowledge of the Park vector is as much as necessary to generate the field in the air gap.

The four‐phase systems methodological analysis presented in this paper is very helpful for the formalization of the theoretical and applicative methodologies necessary for the development of four‐phase systems in a systematic and unified way.

The four‐phase systems analysis is presented in this paper both for the sinusoidal and the variable conditions. Furthermore, the role of the pseudozero‐sequence component, not present in three‐phase case, and its implications in circuital terms have been investigated with attention. Finally, the energetic side and the definition of the correspondent instantaneous and average powers have been investigated as well.

The highly competitive electronics manufacturing marketplace demands that suppliers provide low‐cost, high‐quality products to their customers in a timely fashion. Shortened product life cycles and increasingly global competition have caused traditional manufacturers to focus on their company core competencies, such as product design and development, choosing to outsource the actual manufacturing of their products to contract manufacturers. Although the decision to outsource can have both positive and adverse effects on key areas of the manufacturing supply chain, one positive effect is that the manufacturer’s supply chain agility is increased. Outsourcing has caused an increase in the amount of information that is shared between supply chain partners. As a result, a greater reliance on suppliers and alliance partners has become essential for company survival. We examine the ways in which contract manufacturing has increased the agility of the electronics manufacturing supply chain.

In the field of planetary exploration, the legged-type lander is a common landing buffer device. There are two important performance metrics for legged-type landers: the energy absorption capacity and landing stability. In this paper, a novel method is proposed to optimize the honeycomb buffer of a legged-type lander. Optimization design variables are the dimension parameters of honeycomb and the objective functions are the evaluation parameters of the above two performance metrics.

A multi-body dynamic model of a lander and a finite-element model of the metal honeycomb are established. Based on the simulation results of the finite-element model and the quartic polynomial, the surrogate models are established to evaluate the energy absorption capacity of honeycomb. Considering both the multi-body dynamic model and the surrogate models, the study designed the optimization flow of dimension parameters of honeycomb. Besides, the non-dominated sorting genetic algorithm II is used for iterative calculation.

Images of surrogate models show the monotonous functional relationship between the honeycomb’s energy absorption characteristics and its dimension parameters. Optimization results show an apparent contradiction among the objective functions. Besides, according to the simulation results, this method can significantly improve the comprehensive performance of the lander.

The novel method can effectively reduce the cost of honeycomb compression tests and improve the lander’s design. Therefore, it can be used for optimizing buffers of other types of legged-type landers.

The purpose of this paper is to present the results of the application of various models to estimate the reliability in railway repairable systems.

The methodology proposed by the International Electrotechnical Commission (IEC), using homogeneous Poisson process (HPP) and non-homogeneous Poisson process (NHPP) models, is adopted. Additionally, renewal process (RP) models, not covered by the IEC, are used, with a complementary analysis to characterize the failure intensity thereby obtained.

The findings show the impact of the recurrent failures in the times between failures (TBF) for rejection of the HPP and NHPP models. For systems not exhibiting a trend, RP models are presented, with TBF described by three-parameter lognormal or generalized logistic distributions, together with a methodology for generating clusters.

For those systems that do not exhibit a trend, TBF is assumed to be independent and identically distributed (i.i.d.), and therefore, RP models of “perfect repair” have to be used.

Maintenance managers must refocus their efforts to study the reliability of individual repairable systems and their recurrent failures, instead of collections, in order to customize maintenance to the needs of each system.

The stochastic process models were applied for the first time to electric traction systems in 23 trains and to 40 escalators with ten years of operating data in a railway company. A practical application of the IEC models is presented for the first time.

The purpose of this paper is to present an analysis of how different sourcing policies and resource usage affect the operational performance dynamics of warehouse processes.

The system dynamics (SD) methodology is used to model warehouse operations at the distribution centre of a leading fast‐fashion vertical retailer. This case study includes a detailed analysis of the relationships between the flow of items through the warehouse, the assignment of staff, the inventory management policy, and the order processing tasks.

Case scenario simulations are provided to define warehouse policies enabling increased efficiency, cost savings, reduced inventory, and shorter lead‐times.

The case study reaffirms that a flexible usage of human resources, outsourcing of selected warehouse operations, and sourcing from reliable manufacturers may result in important performance improvements for centralised warehousing.

It is proved that SD is a valuable tool in the field of operations management, not only to support strategic evaluations but also to execute a detailed analysis of logistical processes and make scenario‐based dynamic decisions at the operational level.

Asteroids have the characteristics of noncooperative, irregular gravity and complex terrain on the surface, which cause difficulties in successful landing for conventional landers. The purpose of this paper is to study the trajectory tracking problem of a multi-node flexible lander with unknown flexible coefficient and space disturbance.

To facilitate the stability analysis, this paper constructs a simplified dynamic model of the multi-node flexible lander. By introducing the nonlinear transformation, a concurrent learning-based adaptive trajectory tracking guidance law is designed to ensure tracking performance, which uses both real-time information and historical data to estimate the parameters without persistent excitation (PE) conditions. A data selection algorithm is developed to enhance the richness of historical data, which can improve the convergence rate of the parameter estimation and the guidance performance.

Finally, Lyapunov stability theory is used to prove that the unknown parameters can converge to their actual value and, meanwhile, the closed-loop system is stable. The effectiveness of the proposed algorithm is further verified through simulations.

This paper provides a new design idea for future asteroid landers, and a trajectory tracking controller based on concurrent learning and preset performance is first proposed.