Consumer preference prediction by using a hybrid evidential reasoning and belief rule-based methodology

Belief rule-based methodology for mapping consumer preferences and setting product targets

The main objective of this paper is to propose a new risk priority model for prioritizing failures in failure mode and effects analysis (FMEA) on the basis of fuzzy evidential reasoning (FER) and belief rule-based (BRB) methodology. The technique is particularly intended to resolve some of the shortcomings in fuzzy FMEA (i.e., fuzzy rule-based) approaches. In the proposed approach, risk factors like occurrence (O), severity (S), and detection (D), along with their relative importance weights, are described using fuzzy belief structures. The FER approach is used to capture and aggregate the diversified, uncertain assessment information given by the FMEA team members; the BRB methodology is used to model the uncertainty, and nonlinear relationships between risk factors and corresponding risk level; and the inference of the rule-based system is implemented using the weighted average-maximum composition algorithm. The Dempster rule of combination is then used to aggregate all relevant rules for assessing and prioritizing the failure modes that have been identified in FMEA. A case study concerning an ocean going fishing vessel in a marine industry is provided and conducted using the proposed model to illustrate its potential applications and benefits.

With the rapid development of information technology in inland waterway, radar was widely used to track the ship running, in order to ensure the safe and efficient shipping industry development, as well as to avoid a ship collision causing unnecessary economic losses. For the problem of radar target tracking data associated, a method of data association with radar data was proposed, which was based on radar target course and speed. By this method, the target error or loss problem was solved when the target density was large and used belief rule-based (BRB) methodology to verify the reliability of this method. Real target points obtained by this method had been filtered through particle filter. And then the radar target tracking was achieved. This method has a good target tracking results, verified by Monte Carlo simulations.

The major research studies into success and failure in new product development that have been conducted over the last 40 years are reviewed. These have provided consistent evidence, especially in the management of the development process, of attributes associated with success. It is shown that most of the studies have produced results that are not in a form for easy application by practitioners. A methodology as to how the past lessons may be applied practically is proposed.

Iterative learning belief rule-base inference methodology using evidential reasoning for delayed coking unit

A structural equation model of the impact of the “fuzzy front end” on the success of new product development

Predicting the performance of the new product development and selecting the strategy in the case of new product development failure is an issue that has drawn the attention of the many managers. Therefore, the goal of this study is to design an integrated system of prediction of product development success and selection of a proper market-product strategy by the method of artificial intelligence in companies working in the food industry. The population of this study was 250 companies of the food industries in Iran. The inputs and outputs of the success of the new product development were obtained from the research literature. Moreover, Ansoff matrix was applied to select the market-product strategy. A questionnaire was used to collect the data in this study. The adaptive neural-fuzzy network method and the fuzzy inference system are used to analyze the data. The results show that the Chief Executive Officers of companies working in the food industry may take action to predict a new product development success before developing the new product and use alternative strategies if needed.

Early Supplier Involvement (ESI) aims to facilitate New Product Development (NPD) success and create competitive advantage for the purchasing firm. Unfortunately, empirical results are inconsistent in verifying the linkage between ESI and NPD success. To solve this paradox, this paper views ESI as a knowledge integration process and examines the role of the purchasing firm's integrative capabilities in the process. Competing models are proposed and tested. The results demonstrate that NPD success depends not only on the supplier's knowledge and expertise, but also on the purchasing firm's integrative capabilities to absorb knowledge and increase efficiency of knowledge integration.

Online updating belief rule based system for pipeline leak detection under expert intervention

While creativity is one of the core factors that influence the success of new product development (NPD), its antecedents and consequences on new product development have not yet been fully examined in the literature. Specially, the mediating role of team member’s creativity on NPD success is yet to be clarified. This study thus aims to develop a theoretical framework that integrates the effects of trust, knowledge integration, and team sensemaking capability on team members’ creativity, as well as the mediating effects of team members’ creativity on NPD success. A total of 312 samples were collected from NPD team members working in high-tech firms in Taiwan, using a self-administered survey. The partial least squares (PLS) approach was used to assess the proposed hypotheses. The empirical results show that trust has a significant effect on creativity, knowledge integration, and team sensemaking capability, while knowledge integration and team sensemaking capability have a significant effect on creativity and NPD success. Team members’ creativity mediates the influences of trust, team sensemaking capability, and knowledge integration on NPD success. The results of this study can deepen our understanding of the dynamic role that creativity plays in the NPD process.

This paper illustrates a subjective safety-cost based design-decision support framework using fuzzy logic and evidential reasoning approaches. The framework is divided into three parts. The first one is for safety estimate and synthesis including fuzzy rule-based safety estimate using fuzzy rule-based evidential reasoning (FRB-ER) approach, as well as the safety synthesis using evidential reasoning approach. Considering the cost incurred for the safety improvement in a design option, the second part focuses on synthesising the safety and cost estimates using evidential reasoning approach to obtain the overall evaluation of the whole system for each design option. The third part is to apply the overall evaluation for the design selection. An illustrative example is used to demonstrate the application of the proposed framework.

Increase in world population, changes in disease burdens, creation of new treatment methods, growing interests and quality expectations are enhanced the need and demand for health services and medicine. However, developing original medicines is a challenging and expensive process. For that reason, generally generic drug development activities are carried out in Turkey. On the other hand, technological infrastructure of pharmaceutical industry in Turkey has been strengthened by making the necessary investments in the "Good Manufacturing Practice" framework, which is determined by the World Health Organization. Therefore, the sector has reached a comparable technological level with European countries and nowadays become an important and growing market position. In this study, to examine the process from idea to launch, Abdi İbrahim Pharmaceutical Company's new product development model has been selected and the steps of the model have been defined. Main aim is to examine and evaluate the impact of successful management of the model on the success of new product development which depends on reliability, quality, efficiency, sustainability and profitability. Study revealed that the success of new product development highly depends on not only the effective management of the process but the interdepartmental integration and the value attached to information technologies.

Consumer acceptance of orange juice containing functional ingredients

Remaining useful life (RUL) estimation of aero-engine is a significant part of the aircraft reliability improvement and operational cost reduction. In order to solve the waste of performance data, in this study, a belief rule-based inference methodology using the evidential reasoning (RIMER) based RUL estimation process is proposed. Firstly, we take the principal component analysis (PCA) and the differential evolution (DE) algorithm to optimize the structure and parameter of the belief rule base (BRB), and then estimate the RUL of aero-engine through evidential reasoning (ER) algorithm. The practical case is investigated to validate the feasibility and efficiency of the proposed method. The experimental results show the RIMER based RUL estimation of aero-engine can support decision-making in the fields of aircraft prognostic and health management.

Wireless sensor networks (WSNs) has been developed rapidly in recent years, but with the number of nodes increasing, it is a difficult task to maintain their normal working condition. Maintainability estimation is the core issue in product design and quality improvement. To improve the maintainability of WSNs, it is important to design a maintainability estimation method. In this paper, we propose a maintainability estimation method for WSNs using belief rule base (BRB) system. The conception and connotation of maintainability are discussed and a process of design for maintainability (DFM) is proposed. Taking account of whole WSNs lifetime, the antecedent attributes influencing maintainability are investigated, which include design factor and external factor. We also establish the BRB base on expert knowledge, which contains three sub-rule-bases. Finally, using the evidential reasoning approach, the nonlinear relationship between maintainability and the antecedent attributes is deduced. By predicting maintainability of a new product using the nonlinear relationship, this maintainability estimation method can provide a theoretical guidance in the design of WSNs.