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This study aims to focus on proposing a new memory-type chart called progressive mean exponentially weighted moving average (PMEWMA) control chart. This memory-type chart is an improvement on the existing progressive mean control chart, to detect small and moderate shifts in a process.

The PMEWMA control chart is developed by using a cumulative average of the exponentially weighted moving average scheme known as the progressive approach. This scheme is designed based on the assumption that data follow a normal distribution. In addition, the authors investigate the robustness of the proposed chart to the normality assumption.

The variance and the mean of the scheme are computed, and the mean is found to be an unbiased estimator of the population mean. The proposed chart's performance is compared with the existing charts in the literature by using the average run-length as the performance measure. Application examples from the petroleum and bottling industry are also presented for practical considerations. The comparison shows that the PMEWMA chart is quicker in detecting small shifts in the process than the other memory-type charts covered in this study. The authors also notice that the PMEWMA chart is affected by higher kurtosis and skewness.

A new memory-type scheme is developed in this research, which is efficient in detecting small and medium shifts of a process mean.

The purpose of this study is to develop a joint production, maintenance and quality control strategy involving a periodic preventive maintenance policy.

The proposed integrated policy is defined and modeled mathematically.

The paper focuses on finding simultaneously the optimal values of the preventive maintenance period, the buffer stock size, the sample size, the sampling interval and the control chart limits, such that the expected total cost per time unit is minimized.

The paper attempts to integrate in a single model the three main aspects of any manufacturing system: production, maintenance and quality. The considered system consists of one machine subject to a degradation process that directly affects the quality of products. The process and product quality control is carried out using an “x-bar” control chart. In the proposed model, a preventive maintenance action is performed every α inspections of product quality in order to reduce the shift rate to the “out-of-control” state. A corrective maintenance action is undertaken once the control limits are exceeded. In order to palliate perturbations caused by the stopping of the machine to undergo maintenance actions, a buffer stock is built up to ensure the continuous supply of the subsequent machine. The main goal of this work is to develop a model that captures the underlying link between the preventive maintenance policy, the buffer stock size and the parameters of an “x-bar” control chart used to control the quality of the product. Numerical experiments and a study of the effects of the input parameters variation on the obtained results are performed.

The existing models that simultaneously consider maintenance, inventory and control charts consist of a condition-based maintenance (CBM) policy. Periodic preventive maintenance (PM) has not been considered in such models. The proposed integrated model is original, in that it links production through buffer stocks, quality through a control chart and maintenance through periodic preventive maintenance (different practical settings and modeling approach than when CBM is used). Hence, this paper addresses practical situations where, for economic or technical reasons, only systematic periodic preventive maintenance is possible.

The purpose of this paper is to investigate the variety of affective emotions that are evoked in extant project management (PM) practitioners by various PM artefacts.

A phenomenological methodology is used for eliciting, through self‐reporting and observation of gesture, the affective responses and consequential emotions experienced by PM practitioners as they interact or recount previous interactions with various artefacts of PM.

This paper suggests that PM is prevalent in the Western corporate environment because project managers obtain an emotional affect from aspects of the PM experience, and project managers utilise various PM artefacts to emotionally manipulate their environment to their own advantage.

The paper argues for a PM environment which is founded on evidence‐based practices. It suggests that future research should explore the links between PM, social architecture and flow theory.

This paper advances the evolutionary framework for PM research.

The focus of this paper is on life‐cycle objective‐based project management systems in general, and SPMIS in particular. SPMIS (short for Smart Project Management Information System), has been designed: (a) to facilitate the employment of life‐cycle objective‐based project management approaches; and (b) to support concurrent engineering and construction, thus promoting greater integration of the processes under which projects are proposed and implemented. In order to validate the functions designed for SPMIS the authors undertook a detailed case study of a large capital project. The actual project management functions employed by the project team on the case project were researched and charted using the best current PM practices as the guide. While this field research shed light on the actual needs and requirements, the design of the SPMIS functions was approached from first principles in order to incorporate the basic shift from the traditional objectives of cost, time, and quality to life‐cycle objective functions, such as return on investment, facility operability, and life‐cycle integration. This paper describes the fundamental philosophy and framework for the development of life‐cycle objective function‐based project management systems in general, and contrasts these with the existing PM methods.

The purpose of this study is to explore the total quality management (TQM) practices and identify their effect on the nonfinancial performance (NFP) in the automotive engineering industry in Ethiopia. Despite many studies investigating the relationship between TQM practices and NFP, rare research has been conducted on TQM in automotive industries, making this a hugely unexplored field.

The data underlying this study was collected using more than 500 self-administered questionnaire survey, distributed to the employees working under different departments and factories under one automotive engineering industry. Extensive data screening and refinement processes for discarding irrelevant items for the questionnaire (Likert five-point scale) were carried out. The data was employed to test the proposed theoretical model, established with the objective of assessing the effect of TQM practices on the NFP in the case industry. Empirical validated relations have been proofed for previously done researches that there were positive relations between the TQM practices and NFP. Different statistical tools applied include descriptive data analysis, correlation analysis, mean scale test, reliability analysis and factor analysis, and finally, two models were developed based on structural equation modeling by using SPSS and AMOS-26 software.

Results found in this study were quite surprising. Initially, there was a total of ten TQM factors. The six independent factors survived from factor analysis only two factors (employee involvement and innovation) were contributing to the NFP. The study was acted as a performance evaluation system to track the industry NFP. Although the study focused on the effect of TQM practices, for more results it is recommended to conduct a 360-degree further research study to reveal the weaknesses, strengths, opportunities and challenges of the case industry performance.

Every research has its own limitations. The way the analysis is conducted in this study ensures that the limitations do not compromise the validity of the results obtained. Control variables (industry type, size, age, process type and technology used) are not considered in the research which may affect the results obtained. The study included the automobile industry alone, so the obtained results cannot be generalized to other industries.

The positive relationship between the TQM practices and NFP measures indicates the importance of each of these practices in improving the industry. Researchers/managers/practitioners can use this developed model periodically to understand where the industry stands in the quality management journey. They can also analyze the effect of TQM practices on financial as well as operational performance measures. The research findings can also motivate the top management of the industry for better planning of goals, to arrange resources in time, in pursuit of improving quality, employee and industry performance.

The Ethiopian manufacturing industry is required to improve their manufacturing and service quality, in order to enhance their productivity and boost their competitiveness in an international market, which is the basis of this study. This study signifies one of the first attempts to empirically explore this linkage between TQM and performance in the Ethiopian automotive industry context.

Making decisions on preventive maintenance (PM) policy and buffer sizing, as is often studied, may not result in overall optimization. The purpose of this paper is to propose a joint model that integrates PM and buffer sizing with consideration of quality loss for a degenerating system, which aims to minimize the average operation cost for a finite horizon. The opportunistic maintenance (OM) policy which could increase the output and decrease the cost of the system is also explored.

A joint PM and buffer size model considering quality loss is proposed. In this model, the time-based PM and the condition-based PM are taken on the upstream and the downstream machine, respectively. Further, the OM policy based on the theory of constraints (TOC) is also considered. An iterative search algorithm with Monte Carlo is developed to solve the non-linear model. A case study is conducted to illustrate the performance of the proposed PM policies.

The superiority of the proposed integrated policies compared with the separate PM policy is demonstrated. Effects of the policies are testified. The advantages of the proposed TOC-based OM policy is highlighted in terms of low-cost and high-output.

Few studies have been carried out to integrate decisions on PM and buffer size when taking the quality loss into consideration for degenerating systems. Most PM models treat machines equally ignoring the various roles of them. A more comprehensive and integrated model based on TOC is proposed, accompanied by an iterative search algorithm with Monte Carlo for solving it. An OM policy to further improve the performance of system is also presented.

In order to shed light on the implications of the business intelligence (BI) for management accounting (MA) and decision making, this study investigates as to how the use of the BI affects the production, transmission, and reception of performance measures (PM).

To investigate the issue at hand, a case study of an Italian company is carried out. The case study method is deemed suitable to explore the complex, penetrating, and unpredictable relationship between BI and PM.

The case analysis shows that the use of the BI can affect the production of PM by leading the organization to frame PM into an indicator setting. Moreover, the BI can affect the transmission by introducing a new, “visual” approach for presenting PM to decision makers, which is also relevant in the reception as a mobilizing factor.

This study contributes to improving the understanding of BI implications for MA and decision making, which is still limited in the accounting academia. Additionally, this research adds to extant knowledge about the relationship between measurement and management; more specifically, it contributes to understanding the “fate” of PM.

Furthermore, the findings illustrated in this chapter can be relevant from a practical point of view: by showing the role that BI solutions can play in producing and transmitting PM, the study shows the potential contribution of the use of the BI in managing and overcoming problems arising in these phases, favoring the use of these measures.

The purpose of this paper is to examine power relations embedded in verbal and non-verbal medication communication processes that involve nurses, doctors, pharmacists and patients in two general medical wards of an acute care hospital.

This paper reports on the findings of an ethnographic study investigating medication communication processes in hospital spatial environments. It was theoretically informed by the work of Norman Fairclough. Data collection methods comprising video-recordings and video reflexive focus groups were employed. Fairclough's critical discourse analytic framework guided data analysis.

Four different forms of power relations between clinician-patient, nurse-doctor, clinician-organisation and multidisciplinary interactions were uncovered. Nurses asserted their professional autonomy when communicating with doctors about medications by offering specific advice on medical prescribing and challenging medication decisions. Video reflexivity enabled nurses to critically examine their contribution to medication decision-making processes. Clinicians of different disciplines openly contested the organisational structure of patient allocation during medical discussions about management options. Clinicians of different disciplines also engaged in medication communication interchangeably to accomplish patient discharge.

An investigation of existing power relations embedded in medication communication processes within specific clinical contexts can lead to a better understanding of medication safety practices. Video reflexive focus groups are helpful in encouraging clinicians to reflect on their practice and consider ways in which it could be improved in how power relations are played out.

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Index by subjects, compiled by K.G.B. Bakewell covering the following journals: Facilities Volumes 8‐17; Journal of Property Investment & Finance Volumes 8‐17; Property Management Volumes 8‐17; Structural Survey Volumes 8‐17.