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This paper aims to analyze the accuracy of the single and two-phase numerical methods for calculation of ferrofluid convective heat transfer in the presence of a magnetic field. The findings of current study are compared with previous single-phase numerical results and experimental data. Accordingly, the effect of various parameters including nanoparticles concentration, Reynolds number and magnetic field strength on the performance of the single and two-phase models are evaluated.

A two-phase mixture numerical study is carried out to investigate the influence of four U-shaped electromagnets on the hydrodynamic and thermal characteristics of Fe₃O₄/Water ferrofluid flowing inside a heated channel.

It is observed that the applied external magnetic field signifies the convective heat transfer from the channel surface, despite local reduction at a few locations. The maximum heat transfer enhancement is predicted as 23% and 25% using single and two-phase models, respectively. The difference between the results of the two models is mainly attributed to the slip velocity effect which is accounted for in the two-phase model. The magnetic field gradient leads to a significant increase in the slip velocity which in turn causes a slight difference in velocity and temperature profiles obtained by the single and two-phase models in the magnetic field region. According to percentage error calculation, the two-phase method is generally more accurate than the single-phase method. However, the percentage error of both models improves by decreasing either magnetic field intensity or Reynolds number.

For the first time in the literature, to the best of the authors’ knowledge, the current work analyzes the accuracy of the single and two phase numerical methods for calculation of ferrofluid convective heat transfer in the presence of a magnetic field.

Presents validation of the Eulerian approach for unsteady two‐phase flows, whose behaviour depends on the coupling between the two phases, on the basis of the study of attentuation and dispersion of an acoustic wave propagating into a one dimensional two‐phase flow. This approach and the corresponding numerical aspects are accurate enough for later applications in more complex geometries, where “vortex shedding” phenomena take place. Attenuation and dispersion of a pressure wave in a two‐phase medium of rest was previously studied by Temkin and Dobbins. Present work is an extension of this theory to the case of a two‐phase flow. This theoretical approach leads to a numerical solution of the problem. Compares the derived results with those obtained from a direct numerical simulation based on MacCormack scheme in a finite volume formulation. Verifies that analytical and numerical approaches are in good agreement.

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.

The purpose of this paper is to describe the development and application of a numerical model for analysis of flow boiling phenomena and heat transfer.

For flow boiling processes, the fluid and vapour flow regimes in connection with the conjugate heat and mass transfer problem for specimen quenching through the entire boiling curve is modelled. Vaporisation and recondensation, the vapour fraction distribution and vapour movement with respect to the liquid are considered in the calculation of the two‐phase flow and heat transfer process. The derived flow boiling model is based on a mixture model and bubble crowding model approach for two‐phase flow. In addition to the conventional mixture model formulation, here special model implementations have been incorporated that describe: the vapour formation at the superheated solid‐liquid interface, the recondensation process of vapour at the subcooled vapour‐liquid interface, the mass transfer rate in the different boiling phases and the microconvection effect in the nucleate boiling phase resulting from bubble growth and detachment.

The model prediction results are compared with experimental data for quenching of a circular cylinder, showing good agreement in boiling state and heat transfer coefficient distribution. Simulation and experiments lead to a better understanding of the interaction of incident flow in the boiling state and the resulting heat transfer.

Fluid temperatures in the range of 300‐353 K and specimen wall temperatures up to 1,000 K are considered.

Flow boiling is an efficient heat transfer process occurring in several technical applications. Application background of the model development is in quenching of complex metallic specimen geometries in liquids subject to fast changing heat fluxes.

A general model for the complex two‐phase boiling heat transfer at high wall temperatures and fast flow conditions that can be used in engineering applications does not yet exist. The results provide detailed information describing the non‐uniform phase change during the complete quenching process from film boiling to pure convection.

The purpose of this paper is to present a two‐phase approach for designing an efficient tailored but flexible storage solution for resource description framework (RDF) data based on its query workload characteristics.

The approach consists of two phases. The vertical partitioning phase which aims of reducing the number of join operations in the query evaluation process, while the adjustment phase aims to maintain the efficiency of the performance of the query processing by adapting the underlying schema to cope with the dynamic nature of the query workloads.

The authors perform comprehensive experiments on two real‐world RDF datasets to demonstrate that the approach is superior to the state‐of‐the‐art techniques in this domain.

The main motivation behind the authors' approach is that several benchmarking studies have recently shown that each RDF dataset requires a tailored table schema in order to achieve efficient performance during query processing. None of the previous approaches have considered this limitation.

This study aims to investigate numerically the problem of conjugate conduction and mixed convection heat transfer of a nanofluid in a rotational/stationary circular enclosure using a two-phase mixture model.

Hot and cold surfaces on the wall or inside the enclosure (heater and cooler) are maintained at constant temperature of T_h and T_c, respectively, whereas other parts are thermally insulated. To examine the effects of various parameters such as Richardson number (0.01 = Ri =100), thermal conductivity ratio of solid to base fluid (1 = K_r = 100), volume fraction of nanoparticle (0 = φ = 0.05), insertion of conductive covers (C.Cs) around the heater in a different shape (triangular, circular or square), segmentation and arrangement of the conductive blocks (C.Bs) and rotation direction of the enclosure on the flow structure and heat transfer rate, two-dimensional equations of mass, momentum and energy conservation, as well as volume fraction, are solved using finite volume method and Semi-Implicit Method for Pressure Linked Equations (SIMPLE) algorithm.

The results show that inserting C.C around heater can increase or decrease heat transfer rate, and it depends on thermal conductivity ratio of solid to pure fluid. Also, it is found that by the division of C.B and location of its portions in a horizontal configuration, heat transfer rate reduces. Moreover, it is observed that external heating and cooling of the enclosure causes enhancement of heat transfer relative to that of internal heating and cooling. Finally, results illustrate that under the condition that cylinders rotate in the same direction, the heat transfer rate increases as compared to those that rotate in the opposite direction. Hence rotation direction of cylinders can be used as a desired parameter for controlling heat transfer rate.

A comprehensive report of results for the problem of conjugate conduction and mixed convection heat transfer in a circular cylinder containing different shapes of C.C, conducting obstacle and heater and cooler has been presented. An efficient numerical technique has been developed to solve this problem. The achievements of this paper are purely original, and the numerical results were never published by any researcher.

The planning approach used is issue‐based planning or formal strategic planning, leading to local optimization and duplicated redundancy. An approach is presented in the rapid growth of the business scale which emphasizes both customization and effectiveness, not only operation efficiency. The paper addresses these issues.

A two‐phase approach is applied to obtain a smooth implementation. A lean operation concept is executed in the first phase to reduce the engineer's workload, and the business process re‐engineering (BPR) technique is used in phase two to transform the working model.

This paper presents an extension model of hoshin kanri to translate strategies into achievable policies and actions to fulfil the objectives of the enterprise. This model not only comprises a complete plan and executive structure which is simple and effective, but also conducts complicated communication processes at different levels to achieve the common goals as envisioned by the executive management.

A case study is introduced to show the complete policy deployment process and realize the actual “vital few”. This study has been successfully implemented in the case company, and the labor productivity was improved by 6 percent over a two‐year period.

The paper presents a successful application of hoshin kanri for a semiconductor manufacturing company within a rapid growth environment.

The aim of this paper is to explore the role of Six Sigma performance measurement at both strategic and operational levels within call centres where the definition of Six Sigma is widened to include systems thinking constructs.

A two‐phase methodology is used involving two call centre cases within a call centre group. Phase 1 establishes the need for Six Sigma customer‐based measures in addition to internal performance measures and phase 2 studies the implementation of this wider set of Six Sigma performance measures.

The development and application of Six Sigma performance measures that cover both strategic and operational performance measures lead to a more sustainable approach to business improvement, rather than traditional call centre internal performance measures which may be misleading for the overall performance of the call centre.

The development of the strategic and operational, or double, DMAIC approach offers opportunities for developing wider applications in service contexts using customer‐orientated performance measures.

If call centres rely solely on internal performance measures, a misleading picture of call centre performance may be obtained. There is a need to apply Six Sigma to cover both strategic and operational performance measures.

A combined strategic and operational approach to Six Sigma has been developed which enables service‐based organisations (call centres) to develop sustainable business improvement.

Cloud computing is a major enabling technology for Industry 4.0 and the Big Data era. However, cloud-based firms, who establish their businesses on cloud platforms, have received scant attention in the extant operations management (OM) literature. To narrow this gap, the purpose of this paper is to investigate cloud-based firms from an operations strategy perspective.

A two-phase multi-method approach was adopted. In the first phase, content analysis of 27 reports from cloud-based firms was conducted, aided by text mining keyword extraction. Two data-related operations capabilities were identified and hypotheses were posited regarding the relationships between data resources (DR), operations capabilities and firm growth (FG). In the second phase, a sample of 190 cloud-based firms was collected. Seemingly unrelated regression and bootstrapping method were employed to test the proposed hypotheses using the survey data.

The content analysis indicates data as a key resource and both data processing capability and data transformational capability as critical operations capabilities of cloud-based firms. FG is regarded as a top priority in the cloud context. The regression results indicate that DR and the two capabilities contribute to the growth of cloud-based firms. Moreover, a follow-up bootstrapping analysis reveals that the mediating effects of the two capabilities vary between different types of FG.

To the authors’ best knowledge, this is one of the first OM studies on cloud-based firms. This study extends the operations strategy literature by identifying and testing the key operations capabilities and priorities of cloud-based firms. It also provides insightful implications for industrial practitioners.

The adverse interactions between disruptions can increase the supply chain's vulnerability. Accordingly, establishing supply chain resilience to deal with disruptions and employing business continuity planning to preserve risk management achievements is of considerable importance. The aforementioned idea is discussed in this study.

This study proposes a multi-objective optimization model for employing business continuity management and organizational resilience in a supply chain for responding to multiple interrelated disruptions. The improved augmented e-constraint and the scenario-based robust optimization methods are adopted for multi-objective programming and dealing with uncertainty, respectively. A case study of the automotive battery manufacturing industry is also considered to ensure real-world conformity of the model.

The results indicate that interactions between disruptions remarkably increase the supply chain's vulnerability. Choosing a higher fortification level for the supply chain and foreign suppliers reduces disruption impacts on resources and improves the supply chain's resilience and business continuity. Facilities dispersion, fortification of facilities, lateral transshipment, order deferral policy, dynamic capacity planning and direct transportation of products to markets are the most efficient resilience strategies in the under-study industry.

Applying resource allocation planning and portfolio selection to adopt preventive and reactive resilience strategies simultaneously to manage multiple interrelated disruptions in a real-world automotive battery manufacturing industry, maintaining the long-term achievements of supply chain resilience using business continuity management and dynamic capacity planning are the main contributions of the presented paper.