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Article
Publication date: 30 March 2023

Rafael Diaz and Ali Ardalan

Motivated by recent research indicating that the operational performance of an enterprise can be enhanced by building a supporting data-driven environment in which to operate…

Abstract

Purpose

Motivated by recent research indicating that the operational performance of an enterprise can be enhanced by building a supporting data-driven environment in which to operate, this paper presents a simulation framework that enables an examination of the effects of applying smart manufacturing principles to conventional production systems, intending to transition to digital platforms.

Design/methodology/approach

To investigate the extent to which conventional production systems can be transformed into novel data-driven environments, the well-known constant work-in-process (CONWIP) production systems and considered production sequencing assignments in flowshops were studied. As a result, a novel data-driven priority heuristic, Net-CONWIP was designed and studied, based on the ability to collect real-time information about customer demand and work-in-process inventory, which was applied as part of a distributed and decentralised production sequencing analysis. Application of heuristics like the Net-CONWIP is only possible through the ability to collect and use real-time data offered by a data-driven system. A four-stage application framework to assist practitioners in applying the proposed model was created.

Findings

To assess the robustness of the Net-CONWIP heuristic under the simultaneous effects of different levels of demand, its different levels of variability and the presence of bottlenecks, the performance of Net-CONWIP with conventional CONWIP systems that use first come, first served priority rule was compared. The results show that the Net-CONWIP priority rule significantly reduced customer wait time in all cases relative to FCFS.

Originality/value

Previous research suggests there is considerable value in creating data-driven environments. This study provides a simulation framework that guides the construction of a digital transformation environment. The suggested framework facilitates the inclusion and analysis of relevant smart manufacturing principles in production systems and enables the design and testing of new heuristics that employ real-time data to improve operational performance. An approach that can guide the structuring of data-driven environments in production systems is currently lacking. This paper bridges this gap by proposing a framework to facilitate the design of digital transformation activities, explore their impact on production systems and improve their operational performance.

Details

Industrial Management & Data Systems, vol. 123 no. 5
Type: Research Article
ISSN: 0263-5577

Keywords

Article
Publication date: 2 May 2023

Kirt Hainzer, Catherine O'Mullan and Philip Hugh Brown

Agricultural extension has played a central role in building the capacity of smallholders for decades. In efforts to improve extension outcomes, demand-driven approaches have…

Abstract

Purpose

Agricultural extension has played a central role in building the capacity of smallholders for decades. In efforts to improve extension outcomes, demand-driven approaches have emerged to better align extension content with smallholder context. The aim of this paper is to explore the challenges facing demand-driven extension in Papua New Guinea.

Design/methodology/approach

Exploratory case study methodology was used to explore the challenges facing demand-driven extension from the perspectives of 11 practitioners experienced in community engagement in Papua New Guinea.

Findings

Although there is great potential for demand-driven extension, this research found extension services in Papua New Guinea are ill-equipped to introduce and sustain a resource-intensive approach like demand-driven extension. It further found that rural farmers who extension organisations have long neglected lack the necessary skills and trust to gain from these services.

Research limitations/implications

A limitation of this research is that it only reflects the opinions of practitioners working in Papua New Guinea. Further research featuring a broader sample of value chain actors connected to extension would provide a more complete understanding of the potential challenges to demand-driven engagement in this context.

Originality/value

With a growing interest among development projects to utilise demand-driven engagement with farmers, this research is the first study to explore the challenge facing this promising approach in Papua New Guinea.

Details

Journal of Agribusiness in Developing and Emerging Economies, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2044-0839

Keywords

Article
Publication date: 1 June 2022

Sagarika Rout and Gyan Ranjan Biswal

Notable energy losses and voltage deviation issues in low-voltage radial distribution systems are a major concern for power planners and utility companies because of the…

Abstract

Purpose

Notable energy losses and voltage deviation issues in low-voltage radial distribution systems are a major concern for power planners and utility companies because of the integration of electric vehicles (EVs). Electric vehicle charging stations (EVCSs) are the key components in the network where the EVs are equipped to energize their battery. The purpose of this paper is coordinating the EVCS and distributed generation (DG) so as to place them optimally using swarm-based elephant herding optimization techniques by considering energy losses, voltage sensitivity and branch current as key indices. The placement and sizing of the EVCS and DG were found in steps.

Design/methodology/approach

The IEEE 33-bus test feeder and 52-bus Indian practical radial networks were used as the test system for the network characteristic analysis. To enhance the system performance, the radial network is divided into zones for the placement of charging stations and dispersed generation units. Balanced coordination is discussed with three defined situations for the EVCS and DG.

Findings

The proposed analysis shows that DG collaboration with EVCS with suitable size and location in the network improves the performance in terms of stability and losses.

Research limitations/implications

Stability and loss indices are handled with equal weight factor to find the best solution.

Social implications

The proposed method is coordinating EVCS and DG in the existing system; the EV integration in the low-voltage side can be incorporated suitably. So, it has societal impact.

Originality/value

In this study, the proposed method shows improved results in terms EVCS and DG integration in the system with minimum losses and voltage sensitivity. The results have been compared with another population-based particle swarm optimization method (PSO). There is an improvement of 18% in terms of total power losses and 9% better result in minimum node voltage as compared to the PSO technique. Also, there is an enhancement of 33% in the defined voltage stability index which shows the proficiency of the proposed analysis.

Details

World Journal of Engineering, vol. 20 no. 6
Type: Research Article
ISSN: 1708-5284

Keywords

Article
Publication date: 15 August 2023

Zul-Atfi Ismail

At the beginning of the Corona Virus Disease 2019 (COVID-19) pandemic, a digitalized construction environments surfaced in the heating, ventilation and air conditioning (HVAC…

Abstract

Purpose

At the beginning of the Corona Virus Disease 2019 (COVID-19) pandemic, a digitalized construction environments surfaced in the heating, ventilation and air conditioning (HVAC) systems in the form of a modern delivery system called demand controlled ventilation (DCV). Demand controlled ventilation has the potential to solve the building ventilation's biggest problem of managing indoor air quality (IAQ) for controlling COVID-19 transmission in indoor environments. However, the improper evaluation and information management of infection prevention on dense crowd activities such as measurement errors and volatile organic compound (VOC) generation failure rates, is fragmented so the aim of this research is to integrate this and explore potentials with machine learning algorithms (MLAs).

Design/methodology/approach

The method used is a thorough systematic literature review (SLR) approach. The results of this research consist of a detailed description of the DCV system and digitalized construction process of its IAQ elements.

Findings

The discussion revealed that DCV has a potential for being further integrated by perceiving it as a MLAs and hereby enabling the management of IAQ level from the perspective of health risk function mechanism (i.e. VOC and CO2) for maintaining a comfortable thermal environment and save energy of public and private buildings (PPBs). The appropriate MLA can also be selected in different occupancy patterns for seasonal variations, ventilation behavior, building type and locations, as well as current indoor air pollution control strategies. Furthermore, the conceptual framework showed that MLA application such as algorithm design/Model Predictive Control (MPC) integration can alleviate the high spread limitation of COVID-19 in the indoor environment.

Originality/value

Finally, the research concludes that a large unexploited potential within integration and innovation is recognized in the DCV system and MLAs which can be improved to optimize level of IAQ from the perspective of health throughout the building sector DCV process systems. The requirements of CO2 based DCV along with VOC concentrations monitoring practice should be taken into consideration through further research and experience with adaption and implementation from the ventilation control initial stage of the DCV process.

Details

Open House International, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0168-2601

Keywords

Article
Publication date: 22 March 2022

Vuong Dai Quach, Mitsuyasu Yabe, Hisako Nomura and Yoshifumi Takahashi

This paper aims to provide empirical insight into the trends and structural changes in meat consumption in Vietnam.

Abstract

Purpose

This paper aims to provide empirical insight into the trends and structural changes in meat consumption in Vietnam.

Design/methodology/approach

This study applies the Quadratic Almost Ideal Demand System model on multiple cross-sectional data sets derived from the Vietnam Household Living Standards Survey (VHLSS) of 2004–2016 and follows a consistent two-step procedure to deal with the zero consumption issue. The estimated demand elasticities are then compared and analyzed over time.

Findings

The empirical results show that in the last decade, meat consumption patterns in Vietnam have undergone a remarkable structural change, with poultry and beef increasingly taking important roles in the meat consumption structure of households. In addition, demographic characteristics, including settlement type, household size and the age of the household head, have significantly influenced meat expenditure patterns in Vietnam.

Research limitations/implications

The paper considers the demand for meat consumed at home but not meat consumed away from home.

Originality/value

In many developing countries, increased disposable income, together with rapid urbanization and international integration, has significantly changed consumers' food consumption behaviors. This is one of the first studies using household survey data, which permits the exploration of heterogeneous preferences between consumers, to explore structural changes in food consumption patterns in Vietnam.

Details

Journal of Agribusiness in Developing and Emerging Economies, vol. 13 no. 4
Type: Research Article
ISSN: 2044-0839

Keywords

Article
Publication date: 8 March 2022

Ibrahim Mashal

Smart grid is an integration between traditional electricity grid and communication systems and networks. Providing reliable services and functions is a critical challenge for the…

Abstract

Purpose

Smart grid is an integration between traditional electricity grid and communication systems and networks. Providing reliable services and functions is a critical challenge for the success and diffusion of smart grids that needs to be addressed. The purpose of this study is to determine the critical criteria that affect smart grid reliability from the perspective of users and investigate the role big data plays in smart grid reliability.

Design/methodology/approach

This study presents a model to investigate and identify criteria that influence smart grid reliability from the perspective of users. The model consists of 12 sub-criteria covering big data management, communication system and system characteristics aspects. Multi-criteria decision-making approach is applied to analyze data and prioritize the criteria using the fuzzy analytic hierarchy process based on the triangular fuzzy numbers. Data was collected from 16 experts in the fields of smart grid and Internet of things.

Findings

The results show that the “Big Data Management” criterion has a significant impact on smart grid reliability followed by the “System Characteristics” criterion. The “Data Analytics” and the “Data Visualization” were ranked as the most influential sub-criteria on smart grid reliability. Moreover, sensitivity analysis has been applied to investigate the stability and robustness of results. The findings of this paper provide useful implications for academicians, engineers, policymakers and many other smart grid stakeholders.

Originality/value

The users are not expected to actively participate in smart grid and its services without understanding their perceptions on smart grid reliability. Very few works have studied smart grid reliability from the perspective of users. This study attempts to fill this considerable gap in literature by proposing a fuzzy model to prioritize smart grid reliability criteria.

Article
Publication date: 3 April 2023

Sadiya Naaz, Mangey Ram and Akshay Kumar

The purpose of this paper is to evaluate the reliability and structure function of refrigeration complex system consisted of four components in complex manner.

Abstract

Purpose

The purpose of this paper is to evaluate the reliability and structure function of refrigeration complex system consisted of four components in complex manner.

Design/methodology/approach

Although, a variety of methodologies have been used to assess the refrigeration system's reliability function that has proven to be effective, the universal generating function approach is the basis of this research study, which is used in the calculation of a domestic refrigeration system with four separate components that are related in series and parallel with a corresponding sample to form a complex machine.

Findings

In this paper, signature reliability of the refrigeration system has been evaluated with the universal generating function technique. There are four components present in the proposed system in complex (series and parallel) manner. The tail signature, signature, Barlow–Proschan index, expected lifetime and expected cost of independent identically distributed are all computed.

Originality/value

This is the first study of domestic refrigeration system to examine the signature reliability with the help of universal generating function techniques with various measures. Refrigeration systems are an essential process in industries and home applications as they perform cooling or the maintain temperature at the desired value. A cycle of refrigeration consists of four main components such as, heat exchange, compression and expansion with a refrigerant flowing through the units within the cycle.

Article
Publication date: 15 March 2022

Shaoyu Zeng, Yinghui Wu and Yang Yu

The paper formulates a bi-objective mixed-integer nonlinear programming model, aimed at minimizing the total labor hours and the workload unfairness for the multi-skilled worker…

Abstract

Purpose

The paper formulates a bi-objective mixed-integer nonlinear programming model, aimed at minimizing the total labor hours and the workload unfairness for the multi-skilled worker assignment problem in Seru production system (SPS).

Design/methodology/approach

Three approaches, namely epsilon-constraint method, non-dominated sorting genetic algorithm 2 (NSGA-II) and improved strength Pareto evolutionary algorithm (SPEA2), are designed for solving the problem.

Findings

Numerous experiments are performed to assess the applicability of the proposed model and evaluate the performance of algorithms. The merged Pareto-fronts obtained from both NSGA-II and SPEA2 were proposed as final solutions to provide useful information for decision-makers.

Practical implications

SPS has the flexibility to respond to the changing demand for small amount production of multiple varieties products. Assigning cross-trained workers to obtain flexibility has emerged as a major concern for the implementation of SPS. Most enterprises focus solely on measures of production efficiency, such as minimizing the total throughput time. Solutions based on optimizing efficiency measures alone can be unacceptable by workers who have high proficiency levels when they are achieved at the expense of the workers taking more workload. Therefore, study the tradeoff between production efficiency and fairness in the multi-skilled worker assignment problem is very important for SPS.

Originality/value

The study investigates a new mixed-integer programming model to optimize worker-to-seru assignment, batch-to-seru assignment and task-to-worker assignment in SPS. In order to solve the proposed problem, three problem-specific solution approaches are proposed.

Details

Kybernetes, vol. 52 no. 9
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 21 July 2023

Tillmann Boehme, Joshua Fan, Thomas Birtchnell, James Aitken, Neil Turner and Eric Deakins

Delivering housing to resource-constrained communities (RCCs) is a complex process beset with difficulties. The purpose of this study is to use a complexity lens to examine the…

Abstract

Purpose

Delivering housing to resource-constrained communities (RCCs) is a complex process beset with difficulties. The purpose of this study is to use a complexity lens to examine the approach taken by a social enterprise (SE) in Australia to develop and manage a housebuilding supply chain for RCCs.

Design/methodology/approach

The research team used a longitudinal case study approach from 2017 to 2022, which used mixed methods to understand the phenomenon and gain an in-depth understanding of the complex issues and problem-solving undertaken by an SE start-up.

Findings

Balancing mission logic with commercial viability is challenging for an SE. The supply chain solution that evolved accommodated the particulars of geography and the needs of many stakeholders, including the end-user community and government sponsors. Extensive and time-consuming socialisation and customisation led to a successful technical design and sustainable supply chain operation.

Practical implications

Analysing supply chain intricacies via a complexity framework is valuable for scholars and practitioners, assisting in designing and developing supply chain configurations and understanding their dynamics. Meeting the housing construction needs of RCCs requires the SE to place societal focus at the centre of the supply chain rather than merely being a system output. The developed business model complements the engineering solution to empower a community-led housing construction supply chain.

Originality/value

This longitudinal case study contributes to knowledge by providing rich insights into the roles of SEs and how they develop and operate supply chains to fit with the needs of RCCs. Adding a contextual response dimension to an established complexity framework helped to explain how hybrid organisations balance commercial viability demands with social mission logic by amending traditional supply chain and governance practices. The case provides insights into supply chain configuration, needed changes and potential impacts when an SE as a focal actor inserts into a traditional for-profit construction supply chain.

Details

Supply Chain Management: An International Journal, vol. 29 no. 1
Type: Research Article
ISSN: 1359-8546

Keywords

Open Access
Article
Publication date: 18 April 2023

Jonas Boström, Helene Hillborg and Johan Lilja

The purpose of this paper is to explore and describe the perspectives and reasoning of senior development leaders in healthcare organizations, when reflecting on design as theory…

1316

Abstract

Purpose

The purpose of this paper is to explore and describe the perspectives and reasoning of senior development leaders in healthcare organizations, when reflecting on design as theory and practice in relation to more traditional methods and tools for improving quality and support innovation.

Design/methodology/approach

The paper is based on a qualitative interview design with five development and innovation leaders from separate healthcare regions in Sweden. They have, to varying degrees, applied design theory and practice for quality improvement and innovation in their organizations. The interview transcript was analysed using a content analysis together with an interpretive approach.

Findings

The major findings are to be found in the balancing act for leadership and organizations in healthcare when it comes to introducing and combining different theories and practices for improving quality and support innovation. The balance is between the change in power dynamics and pushing traditional boundaries in a complex healthcare world.

Practical implications

The narratives from the leaders' experience of applying design theory and practice for improving healthcare quality can help us create readiness and knowledge about how we prevent and/or facilitate planning and implementing design theories, practices, methods and tools in a healthcare context.

Originality/value

The study provides a unique insight when it captures and illustrates five different organizations' experiences when applying design for developing healthcare quality.

Details

The TQM Journal, vol. 35 no. 9
Type: Research Article
ISSN: 1754-2731

Keywords

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