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The purpose of this paper is to develop the C-shaped quality function deployment (QFD) 3D Matrix for service applications.

The C-shaped QFD 3D Matrix proposed by Vezzetti et al. (2016) has been developed for simultaneous analysis of the relationships among three sets of factors of customer requirements, service design characteristics and service performance indicators. The three sets of factors have been determined and based on their interrelationships, 3D and concurrent houses of quality have been formed. Then, service design characteristics and service performance indicators have been prioritized. The obtained priorities have been also compared with traditional concurrent model of QFD.

The findings obtained from the traditional and developed approach seem different, implying that applying the C-shaped QFD 3D Matrix provides a more real perspective of concurrent engineering and the results in different set of priorities of service factors.

The case study was limited to banking services. If the developed approach is used in other institutes, the prioritization of service design characteristics and service performance indicators might be changed.

Compared to Vezzetti et al. (2016) who proposed the C-shaped QFD 3D Matrix for analyzing interrelationships among two customers and a provider, or two providers and a customer, in this paper, the C-shaped QFD 3D Matrix has been developed for analyzing interrelationships among three sets of factors of customer requirements, service design characteristics and service performance indicators.

The purpose of this paper is to propose an integrative approach for improving failure modes and effects analysis (FMEA).

An extensive literature review on FMEA has been performed. Then, an integrative approach has been proposed based on literature review. The proposed approach is an integration of FMEA and quality function deployment (QFD). The proposed approach includes a two-phase QFD. In the first phase, failure modes are prioritized based on failure effects and in the second phase, failure causes are prioritized based on failure modes. The proposed approach has been examined in a case example at the blast furnace operation of a steel-manufacturing company.

Results of the case example indicated that stove shell crack in hot blast blower, pump failure in cooling water supply pump and bleeder valves failed to operate are the first three important failure modes. In addition, fire and explosion are the most important failure effects. Also, improper maintenance, over pressure and excess temperature are the most important failure causes. Findings also indicated that the proposed approach with the consideration of interrelationships among failure effects, failure mode and failure causes can influence and adjust risk priority number (RPN) in FMEA.

As manufacturing departments are mostly dealing with failure effects and modes of machinery and maintenance departments are mostly dealing with causes of failures, the proposed model can support better coordination and integration between the two departments. Such support seems to be more important in firms with continuous production lines wherein line interruption influences response to customers more seriously. A wide range of future study opportunities indicates the attractiveness and contribution of the subject to the knowledge of FMEA.

Although the literature indicates that in most of studies the outcomes of QFD were entered into FMEA and in some studies the RPN of FMEA was entered into QFD as importance rating, the proposed approach is a true type of the so-called “integration of FMEA and QFD” because the three main elements of FMEA formed the structure of QFD. In other words, the proposed approach can be considered as an innovation in the FMEA structure, not as a data provider prior to it or a data receiver after it.

This paper aims to develop a system dynamics (SD) model to identify causal relationships among the elements of failure modes and effects analysis (FMEA), i.e. failure modes, effects and causes.

A causal loop diagram (CLD) has been developed based on the results obtained from interdependencies and correlations analysis among the FMEA elements through applying the integrated approach of FMEA-quality function deployment (QFD) developed by Shaker et al. (2019). The proposed model was examined in a steel manufacturing company to identify and model the causes and effects relationships among failure modes, effects and causes of a roller-transmission system.

Findings indicated interactions among the most significant failure modes, effects and causes. Moreover, corrective actions defined to eliminate or relieve critical failure causes. Consequently, production costs decreased, and the production rate increased due to eliminated/decreased failure modes.

The application of CLD illustrates causal relationships among FMEA elements in a more effective way and results in a more precise recognition of the root causes of the potential failure modes and their easy elimination/decrease. Therefore, applying the proposed approach leads to a better analysis of the interactions among FMEA elements, decreased system's failure rate and increased system availability.

The literature review indicated a few studies on the application of SD methodology in the maintenance area, and no study was performed on the causal interactions among FMEA elements through an FMEA-QFD based SD approach. Although the interactions of these elements are significant and helpful in risks ranking, researchers fail to investigate them sufficiently.

The purpose of this paper is to propose an integrated model of quality function deployment (QFD) and customer relationship management (CRM) for design and delivery processes.

After the literature review, the elements of a CRM business cycle were integrated with different phases in QFD. The proposed model was further developed, based on customer participation in the design and delivery of products/services, as a major stage in CRM in three cases: customer participation in design; delivery; and design and delivery. As a case study, the customer participation in delivery was studied in after‐sale services of the Iran Khodro Co., which is the second major carmaker company in Iran.

The results imply that QFD and CRM are complementary approaches and once they are combined, their capabilities are enhanced and managing customer relationship is empowered. According to the case study, personnel monitoring and human resources management (HRM) have been targeted as the first priorities in process parameters and process control characteristics, respectively.

Although the developed model involves considerable advantages, due to the different matrixes used for QFD, its use might become time consuming and complicated. Also, gathering information from customers and categorizing them respectively play major roles in effective and strategic CRM.

The proposed model provides a means of harnessing the power of the present research innovations and advancements in order to empower customer need assessment, acquisition, development, equity leverage, retention and referrals, as well as prioritization of the features of products/services, processes, and performance indicators, according to the voice of customers.

During the past decade the role of purchasing in global competitiveness has been steadily increasing in importance. Similarly, the role of packaging continues to increase in importance because of its dual function in advertising and shipping. The purpose of this paper is to employ the Quality Function Deployment (QFD) methodology to analyze the common purchasing problem of supplier selection for toothpaste packaging. Thus, a technique well known in quality management is adapted for use in the entirely new context of supplier selection in purchasing.

The paper begins by stipulating the properties necessary for suitable packaging. It then examines the type(s) of packaging necessary to satisfy these properties. Finally, it moves to the selection of a supplier having the necessary properties to provide packaging. The analysis is performed with a QFD construct.

The QFD process led to a rapid identification of those suppliers most capable of providing the product characteristics that met the corporate total value goal at the time of study.

The paper presents a structured management approach to deal with the common problem of supplier selection. In doing so, it provides an approach that may be generalized to solve many types of decision problems confronting operations and supply chain managers.

This paper presents a management approach to the very important area of supplier selection. In doing so, it employs a technique well known in the product design area, but not used in the area of supplier selection, that of Quality Function Deployment (QFD). It extends beyond the dyad in that it brings to bear a powerful technique from the Quality Management discipline to a problem in another discipline, Purchasing.

The purpose of this paper is to examine the application of C-shaped QFD 3D Matrix in comparing process characteristics (PC), performance aspects (PA) and customer requirements, simultaneously and to prioritize the first two sets, respectively.

A three dimensional matrix has been developed with three sets of PC, PA and customers’ requirements and C-shaped matrix has been applied for simultaneous comparison of the dimensions and prioritization of the subsets of PC and PA. The proposed approach has been examined in a post bank.

Findings confirm the possibility of simultaneous comparison and prioritization of the three sets of dimensions of this study in post bank services. In addition, “growth and learning” and “bilateral relationship with suppliers” had the first priorities among PA and PC, respectively.

While the proposed approach has many advantages, filling the matrixes is time-consuming. Since illustrating the 3D matrix was not possible, the matrix was separated into five two-dimensional matrixes.

Compared to the studied literature, the proposed approach is practically new in the post bank services.

The main purpose of this study is to develop a model for prioritizing the critical success factors (CSF) of enterprise resources planning (ERP) based on the enablers of organizational agility (OA).

First, the CSFs of ERP and the enablers of OA have been identified and classified using Decision-Making Trial and Evaluation Laboratory (DEMATEL), and then a three-phase quality function deployment (QFD) model has been designed to prioritize the influencing and influenced criteria. The proposed approach has been examined in the banking sector.

Major findings indicated that organizational structure, IT technology infrastructure, and commitment and support by top managers were selected as indicators with top priority.

Research variables were limited to the enablers of OA and the CSFs of ERP; analysis was time-consuming due to the interconnected multiple QFD phases, and findings were limited to the selected branches of a bank. The bank managers were suggested to enhance their commitment and support toward ERP. Also, it was recommended to the managers to evaluate their organizational structure and empower it as much as possible toward the fulfillment of customers' requirements and customers' expected agility.

The development of the QFD matrices and dividing the factors of each research variables into influencing and influenced factors distinguished this study from the literature.

Explores the application of quality function deployment (QFD) concept in strategic marketing planning. First discusses the literature of quality control concepts and marketing concepts, and the current thinking in strategic marketing planning. Then proposes that the QFD concept can be an ideal approach in the strategic marketing planning. The QFD approach maximizes benefits for both customers and companies in the long run, by first determining the customer’s needs, and then translating these needs into corporate goals and marketing objectives. Based on these goals and objectives, marketing strategies and marketing tactics could be developed and implemented to ensure the customers’ needs are met and company’s objectives are obtained.

The purpose of this paper is to propose an innovative and integrated approach based on service quality measurement (SERVQUAL), quality function deployment (QFD) and failure modes and effects analysis (FMEA) for service quality improvement.

The SERVQUAL scale is used for service quality measurement, QFD is used for service design and FMEA is used to prevent possible failures during service delivery.

A case study in a public hospital in Turkey is performed to show how the proposed approach works in practice. The results of the study show that the proposed approach can be used effectively to assess service quality in practice.

Service quality has become an important issue for service enterprises facing a fiercely competitive environment to provide sustainability. This is the first study that applies an integrated methodology based on SERVQUAL scale, QFD and FMEA to service quality improvement.

The exploratory paper investigates the reasons for the adoption or non‐adoption of quality tools in industry. Although quality tools such as statistical process control and failure mode effect analysis are commonly practiced in manufacturing, the same cannot be said for product development.

We adopted a case study approach in this study, which has been found to be the more suitable approach for exploratory research. Semi‐structured interviews ranging from half an hour to one and a half hours were conducted with seven industrialists and three academics. These industrialists are R&D managers, product development managers, project managers and engineers who have been involved in new product development (NPD) in one way or another.

Building on previous studies, the study identified two categories of factor affecting the adoption of quality tools: internal and external factors. User‐friendliness, usefulness, time, monetary cost, flexibility and popularity of the tools are internal factors which may influence the usage of tools. External factors such as project nature, organization, industries and culture account for the external influence.

By identifying the possible reasons of (non‐)adoption of quality tools in NPD, researchers can better design tools and techniques which would be more readily adopt by companies.