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Silicon sensors are semiconductor devices which transform a physical effect (such as pressure, acceleration, flux) into electrical effects (resistance, capacitance variation). Fabrication of these silicon sensors requires very precise control of the silicon micromachining. Some silicon foundries have adapted their experience in integrated circuit manufacturing to silicon sensor production and thus have reduced the costs and dimensions of the silicon sensors. Standard thick film technology has brought versatility to silicon sensor technology. Silicon sensors mounted on a ceramic substrate give fast development, high performance and low cost to OEMs. An alternative solution is the integrated silicon sensor including sensor and circuitry on the same silicon chip. This has been developed for specific applications.

The use of volunteers is one of the approaches to capacity building, preparedness and the response of the health system in disasters. Appropriate management of volunteers during disasters and emergencies is essential. This study aimed to explain the challenges of volunteer management in the Pandemic COVID-19 in Iran.

Qualitative research was conducted using the content analysis based on the Graneheim method. The participants' selection was done based on purposeful sampling and theoretical sampling until data saturation. Direct field observation and 26 interviews were applied to collect data.

Four categories and 15 sub-categories emerged to describe the challenges of volunteer management during the COVID-19 crisis including policymaking barriers (including legal barriers, insurance and support coverage and risk governance), managerial barriers (including planning, coordinating and organizing, training and awareness, command and leadership and information management and documentation), socio-cultural barriers (personal safety attitude and culture, attitudes and expectations of the community and perspectives on volunteers) and executive-operational barriers (monitoring and evaluation, cost and needs assessment).

It is essential to increase managers', officials' and volunteers' perceptions of COVID19 risk through education and information. Preparing a database for volunteers' information, including non-governmental organization and governmental organization volunteers, planning for needs assessment, establishing a mechanism for recruiting volunteers and using their capacities and appropriate organizing, tracking and monitoring of volunteers can be among effective strategies.

This research aims to examine the relevant literature related to maintenance performance measurement in the manufacturing sector. In the process, innovative approaches and models utilized to measure and manage maintenance performance in manufacturing operational settings are classified and examined. Based on this investigation, future research directions and themes are identified.

A database of 251 peer‐reviewed publications, published during the last 30 years, was utilized for the purpose of this research. The published works included contributions from both practitioners and scholars.

This literature review‐based research revealed important themes related to evolution of maintenance performance management. These themes focus on the effective utilization of maintenance resources, information systems support, and human factor management. Based on this literature review, a conceptual framework, which traces the different operational and organizational facets of the evolution of maintenance performance management, is offered.

Based on the findings of this study, it is concluded that the area of maintenance performance and management is in need of more future systematic research efforts aimed at solidifying theoretical constructs and promoting the utilization of more practical applications.

Findings derived from this investigation have relevant manufacturing implications. In this context, understanding the different approaches to maintenance performance measurement and management, as utilized in manufacturing organizations, is critical to these organizations' performance improvement efforts.

Understanding the types and scopes of the different approaches and models utilized to manage and measure maintenance performance in manufacturing operational settings is important in light of the growing competitiveness of the manufacturing sector.

The purpose of this paper is to examine the underlying strategic intent of quality performance. Specifically, the study aimed to examine the individual impact of differentiation and cost leadership as well as their interaction effect on quality performance.

This study employed a data set drawn from 102 managers of Australian manufacturing firms. Multiple regression analysis with moderating effect was used for analysing the relationship between the competitive strategies and quality performance.

The findings indicated that product quality was predicted by differentiation strategy, but not cost leadership strategy. However, the effect of differentiation on quality was moderated by cost leadership whereby the higher the cost leadership, the stronger the effect.

The small sample size which was dominated by small‐to‐medium sized firms (SMEs) was the major limitation of the study. The sample size and distribution also inhibited the comparison of the results between industry sectors.

The results contribute to a better understanding on how quality can be effectively employed as a base for realising competitive strategy. In particular, the positive interaction between differentiation and cost leadership in predicting quality performance suggests the synergy between the two as well as supporting the cumulative view of competitive strategies.

By testing the interaction effect of differentiation and cost leadership in predicting quality performance, this study advances the previous works on the area which looked at the relationship between quality performance and each of the two competitive strategies separately.

The purpose of this paper is to provide a literature review of the performance measurement (PM) in maintenance. The authors aim to discuss the background and development of the PM for maintenance, besides defining the concept of performance measures for maintenance and the frameworks developed.

A detailed and extensive literature search and study was undertaken by the authors on the concept and definition of PM, performance indicators (PIs), maintenance performance indicators and various performance frameworks. The history and theory of PM over different phases of business and technological developments have been critically examined and analysed in this review paper.

This paper reviews and presents the different PIs and PM frameworks like; balanced scorecard (BSC), performance prism, performance pyramid and performance matrix, etc., and identifies their characteristics and shortcomings. After considering related issues and challenges, frameworks and approaches for the maintenance performance measurement (MPM) are also presented, where the emerging techniques like; emaintenance have also been discussed amongst others. More and more industries are applying the balanced and integrated MPM frameworks for their competitive survivability and sustainability.

The concept, issues and approaches considered for the MPM frameworks can be adapted by the practicing managers, while trying to define and develop an MPM framework for the operation and maintenance activities. The considerations of the advantages and limitations of different frameworks can provide insights to the managers for implementation.

Some literature reviews on MPM and MPM frameworks are available today. This paper makes an attempt to provide a detailed and relevant literature review, besides adding value in this new and emerging area.

Managers are increasingly looking to adopt the Internet of Things (IoT) to include the vast amount of big data generated in their decision-making processes. The use of IoT might yield many benefits for organizations engaged in civil infrastructure management, but these benefits might be difficult to realize as organizations are not equipped to handle and interpret this data. The purpose of this paper is to understand how IoT adoption affects decision-making processes.

In this paper the changes in the business processes for managing civil infrastructure assets brought about by IoT adoption are analyzed by investigating two case studies within the water management domain. Propositions for effective IoT adoption in decision-making processes are derived.

The results show that decision processes in civil infrastructure asset management have been transformed to deal with the real-time nature of the data. The authors found the need to make organizational and business process changes, development of new capabilities, data provenance and governance and the need for standardization. IoT can have a transformative effect on business processes.

Because of the chosen research approach, the research results may lack generalizability. Therefore, researchers are encouraged to test the propositions further.

The paper shows that data provenance is necessary to be able to understand the value and the quality of the data often generated by various organizations. Managers need to adapt new capabilities to be able to interpret the data.

This paper fulfills an identified need to understand how IoT adoption affects decision-making processes in asset management in order to be able to achieve expected benefits and mitigate risk.

The purpose of this paper is to develop a Housing Eligibility Assessment Scoring Method (HEASM) for low-income Urgent Repair Programs (URPs).

In order to develop a practical HEASM that incorporates the prevailing eligibility assessment criteria for low-income URPs, a case study research approach was adopted. Emergent themes and patterns in predominant eligibility assessment criteria and methods are derived from program documents utilized by a successful State Urgent Repair Program (SURP) and its 42 Community Partners operating in the Southeastern region of the USA. Coupled with interviews and the expert analysis of SURP staff, the quantitative analysis of 11,414 repaired homes and literature reviews were used to categorize predominant eligible housing repairs and costs.

The five key eligibility assessment criteria categories that emerged from the data analysis are: location, owner-occupancy, family needs, housing repair, and estimated repair costs. The framework of the proposed HEASM is guided by these five categories.

URP decision makers are provided with a simple, practical, and objective eligibility assessment method that can be easily modified to accommodate the unique eligibility criteria and local program conditions. This method should improve the eligibility assessment, prioritization, and the eventual selection of qualifying applicants. Consequently, the capacity of URPs to provide funding to their targeted populations with the most critical needs would be enhanced. Insights could drive the impetus to modify existing URP.

In order to ensure that an inventory system is performing correctly, management must continually monitor the system and take corrective action as necessary. Only a few previous articles have suggested techniques for monitoring and diagnosing the performance of a reorder point system. Uses statistical process control charts to monitor the systems performance on an ongoing basis. The proposed system is triggered by unplanned stockouts or by a periodic review of each item′s inventory turnover rate. The system then systematically analyses the stockout and the control charts and identifies the causes, which can be fitness‐related and/or operations related. Problems can be quickly diagnosed and corrective action taken so the reorder point system will perform as intended.

The performance of Ardalan′s heuristic is compared with that of Teitz and Bart for the location of service facilities, where performance is assessed in terms of the accuracy of solutions. The comparison is made considering two kinds of location problem: p‐median and p‐median with maximum distance constraints. The results indicate that the Teitz and Bart method generally produces a better solution than the Ardalan method for both problems.

This study aims to investigate the effect of productivity and quality on profitability in the US airline industry.

Airlines operations and performance data were used to determine the effect of productivity and quality on profitability. Correlation and multivariate regression analysis have been used for data analysis.

The results show that labor productivity is the most significant predictor of profitability. On‐time performance has no relationship with profitability. The findings suggest that labor productivity, gas price, average annual maintenance cost and employee salary are significant predictors of profitability. The relationship between labor productivity and employee salary with profitability is positive, while gas price and average annual maintenance cost have a negative relationship with profitability.

The research could be more detailed by taking into account measures of airline safety. Additional measures for service quality could be considered.

Operational performance (labor productivity) is the main source of profitability in the US airline industry followed by customer satisfaction and service quality.

The study captures the performance of the airline industry based on longitudinal data from 1989 to 2008. Previous studies have used either quarterly or monthly observations. Second, the study examines the significance of productivity and quality on profitability. Previous studies have provided little insight regarding the effect of productivity and quality on profitability.