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Supply chain literature highlights the increasing importance of effective supply network configuration decisions that take in to account such realities as market turbulence and demand volatility, as well as ever expanding global production networks. Supply network configurations decisions that account for these contingencies are expected to meet the evolving needs of customers while delivering better...
During the use phase of Product-Service Systems (PSS) various kinds of usage data describing the interaction of user and PSS are collected. This information could be used to design PSS tailored to the needs of the users, but in industry this possibility is not utilized due to a lack of support for the analysis of the data. In this paper we present an approach and a model for systematically integrating...
Every company stores more and more product data. Most of the data are not analyzed and possible findings cannot be used. But the utilization of existing knowledge can make the system development process more efficient. Therefore, this paper focuses on the data analysis of system architectures. It develops a concept to identify patterns between system architectures of different products in a database...
This paper proposes a prediction model for forecasting the hard landing problem. The landing phase has been demonstrated the most dangerous phase in flight cycle for fatal accidents. The landing safety problem has become one of the hot research problems in engineering management field. The study concentrates more on the prediction and advanced warning of hard landing. Firstly, flight data is preprocessed...
We need energy resources to assure performance of mechatronic systems. The performance assurance is of major importance in present systems since it leads to high availability and capability. It also helps to reduce failure occurrence. In the article we want to find the up state time of Li-ion batteries. Results are related to influence of the operating environment at different climatic levels. We...
This paper analyzes the possibility of applying model that is not explicitly incorporate competition in hotel Revenue Management. Three scenarios are evaluated; (i) each seller understands how its own price affects its own demand but does not directly account for how its competitor's price does, (ii) each seller knows the total market size, and tries to learn how its own price affects demand, while...
In these recent years, a new channel of tuition fee payment using Internet banking has been introduced to Indonesian students. However, based on obtained data field, payment method using Internet banking service has turned out to be not quite popular among the students. The development of this study is adapted from Chan and Lu [4] research model about Internet banking service adoption in Hong Kong...
This paper addresses the implementation of Automated Identification Technologies (AIT) to support and manage the maintenance of repairable equipment and components that are intended for relatively long use in echelon inventory system with the aim of optimizing the data allocation in a given automated identification system. The paper presents the development of general model for optimizing the use...
The operational dynamics arising out of the diffusion of solar lamps (a new product) in rural India has been discussed in this paper. Empirical evidence is provided to show that the shortage of product supply adversely affects the diffusion process. The shortage not only delays the diffusion process, but also creates multiple phases of diffusion wherein each phase exhibits distinct new product diffusion...
On account of great significance of financial distress prediction for corporations, it is essential to construct an effective prediction model for managers and investors. Traditional financial distress prediction methods design static models using samples within a period of time, but the static models are insensitive to changes, such as concept drift in financial distress. This paper proposed a dynamic...
This paper proposes a state space model to describe multivariate autocorrelated zero-inflated count series. The model extends the classical zero-inflated Poisson distribution into multivariate cases but is able to impose different zero inflations on different dimensions. Combing the zero inflation with the log-normal mixture of independent Poisson distribution, this model allows for flexible cross-correlations...
Empirical models play an important role in the classification of machinery for scheduling preventive maintenance (PM) activities for machinery in manufacturing firms (MFs). First, this manuscript discusses the development of empirical models for classifying machines in an MF and the structure of each empirical model. Then, it presents the classification of machinery using the developed empirical models...
Setting an optimal inspection plan for fatigue critical offshore piping relies on accurately estimating its remnant fatigue life (RFL). Several modeling approaches, such as knowledge-based, model-based, data-driven, fusion techniques etc., have been used to build RFL models in the past. The aim of this paper is to review these approaches and thereby recommend the most favorable approach for building...
For the high-temperature structure, there exists correlation between the thermal stress and thermal intensity in most cases because of the two-sided effects of temperature. This paper proposes a time-varying response surface method considering correlation between the structural response value and structural response threshold based on Copula models. Firstly, the time-varying model of structural response...
Enterprise Resource Planning (ERP) system provides a facility for the integration of business functions within the organisation. Previous studies proved that the potential benefits that can be obtained from ERP system had not been achieved. ERP system impacts at the individual level such as improved control becomes one of the success dimensions of ERP implementation. The purpose of this study is to...
Machine learning is a hot topic recently. For condition monitoring, the machine learning is mainly used to improve the failure diagnosis accuracy, as the machine learning can provide flexible decision function. This paper firstly discusses the advantage and disadvantage of the state of art condition monitoring methods. It figures out the machine learning techniques follow a general procedure and can...
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