Industrial Projects Research Articles

Evaluating the effective factors of BIM for enhancing the construction interface management

Maintaining the proper interface management among the construction stakeholders is becoming more crucial due to the interconnected nature of construction work. Adopting and implementing building information modelling (BIM) technology can aid in the proper execution of construction projects. Therefore, the main goal of this study is to evaluate the effective factors of BIM using DeLone and McLean’s (DM) model. The DM model's factors evaluate the system or technology in terms of system quality, information quality, service quality, and most importantly, the system's net benefits and user satisfaction. The questionnaire was developed with the expert's opinion and the survey was conducted. As megaprojects have more complicated and various levels of information sharing, this study targeted collecting responses from industrial project practitioners in India. From the survey, a total of 166 responses were obtained. Using these data, the frequency test, reliability test, and the relative importance index (RII) were performed. These effective factors of BIM contribute significantly to project performance improvement through proper interface management and communication among stakeholders. The findings of the study emphasized the importance of user satisfaction and the net benefits of BIM. Thus, this study provides further insights to increase the adoption and implementation of BIM technology.

A Pan-Asian Energy Transition? The New Rationale for Decarbonization Policies in the World’s Largest Energy Exporting Countries: A Case Study of Qatar and Other GCC Countries

Climate change has become a major agenda item in international relations and in national energy policy-making circles around the world. This review studies the surprising evolution of the energy policy, and more particularly the energy transition, currently happening in the Arabian Gulf region, which features some of the world’s largest exporters of oil and gas. Qatar, Saudi Arabia, and other neighboring energy exporters plan to export blue and green hydrogen across Asia as well as towards Europe in the years and decades to come. Although poorly known and understood abroad, this recent strategy does not threaten the current exports of oil and gas (still needed for a few decades) but prepares the evolution of their national energy industries toward the future decarbonized energy demand of their main customers in East and South Asia, and beyond. The world’s largest exporter of Liquefied Natural Gas, Qatar, has established industrial policies and projects to upscale CCUS, which can enable blue hydrogen production, as well as natural carbon sinks domestically via afforestation projects.

Maximizing Waste-to-Energy Potential: Optimizing Batch Torrefaction Reactor of Refused-Derived Fuel for Efficient Gasification

Abstract Refuse-derived fuel (RDF) from municipal solid waste (MSW) is a promising alternative to fossil fuels, but its varied composition can impede direct gasification. This industrial research project conducted a series of batch experiments to assess four key parameters: energy yield, mass yield, energy density, and combustion characteristics in the context of RDF torrefaction. The batch reactor processed RDF samples at temperatures of 250°C, 300°C, and 350°C, each with a 30- minute residence time under an inert atmosphere. In addition, Combustion TGA experiments, involving heating torrefied RDF up to 1000°C at a rate of 20°C/min, provided further insights into the robust combustion properties of the torrefied material. Unlocking the secrets of torrefaction magic, we've achieved remarkable energy content boosts. Torrefaction at 250°C, 300°C, and 350°C led to energy content enhancements of 22%, 29%, and 37%, respectively, compared to the original RDF. Notably, the most favorable energy yield was achieved during torrefaction at 250°C, attributed to both its relatively high energy content and mass yield. At a torrefaction temperature of 250 °C and above, the torrefied RDF samples exhibited heating values comparable to standard coal ranges between 25-35 MJ/kg. It is suggested that torrefaction of RDF is an effective pre-treatment process to be used in entrained flow gasifier due to the improved higher heating value, higher energy density, and superior combustion characteristics, proved by the ignition index, flammability index, and burnout index, highlight the effectiveness of the torrefaction process.

Enabling Seamless Connectivity: Networking Innovations in Wireless Sensor Networks for Industrial Application.

The wide-ranging applications of the Internet of Things (IoT) show that it has the potential to revolutionise industry, improve daily life, and overcome global challenges. This study aims to evaluate the performance scalability of mature industrial wireless sensor networks (IWSNs). A new classification approach for IoT in the industrial sector is proposed based on multiple factors and we introduce the integration of 6LoWPAN (IPv6 over low-power wireless personal area networks), message queuing telemetry transport for sensor networks (MQTT-SN), and ContikiMAC protocols for sensor nodes in an industrial IoT system to improve energy-efficient connectivity. The Contiki COOJA WSN simulator was applied to model and simulate the performance of the protocols in two static and moving scenarios and evaluate the proposed novelty detection system (NDS) for network intrusions in order to identify certain events in real time for realistic dataset analysis. The simulation results show that our method is an essential measure in determining the number of transmissions required to achieve a certain reliability target in an IWSNs. Despite the growing demand for low-power operation, deterministic communication, and end-to-end reliability, our methodology of an innovative sensor design using selective surface activation induced by laser (SSAIL) technology was developed and deployed in the FTMC premises to demonstrate its long-term functionality and reliability. The proposed framework was experimentally validated and tested through simulations to demonstrate the applicability and suitability of the proposed approach. The energy efficiency in the optimised WSN was increased by 50%, battery life was extended by 350%, duplicated packets were reduced by 80%, data collisions were reduced by 80%, and it was shown that the proposed methodology and tools could be used effectively in the development of telemetry node networks in new industrial projects in order to detect events and breaches in IoT networks accurately. The energy consumption of the developed sensor nodes was measured. Overall, this study performed a comprehensive assessment of the challenges of industrial processes, such as the reliability and stability of telemetry channels, the energy efficiency of autonomous nodes, and the minimisation of duplicate information transmission in IWSNs.

Research on the Innovative Development of Heilongjiang's Music Tourism Industry in the Context of the Digital Era

To enhance the influence of Chinese civilization, it is essential to uphold cultural positions steadfastly. This approach enables us to effectively narrate and disseminate Chinese stories and voices, thereby promoting Chinese culture worldwide. Music culture, as a significant component of traditional culture, fosters national pride and cultural confidence when promoted and inherited. Especially in the context of the digital era, leveraging digital technology is crucial to facilitate the harmonious integration of the music and tourism industries. This integration promotes the continuous dissemination and development of the music tourism industry, creating a creative industry and premium entrepreneurial projects in music tourism. This research explores the innovative development paths of Heilongjiang's music tourism industry in the digital era, aiming to provide practical guidance for the innovative development of cultural and tourism industries in other regions of China.

Research on Cultural Industry Project Management from an Innovation Management Perspective

Research on Cultural Industry Project Management from an Innovation Management Perspective

Design, characterizations, and antimicrobial activity of sustainable home furnishing-based waste fabric treated using biobased nanocomposite

Clothing and textile industries are major contributors to environmental pollution including textile manufacturing through garment production, spinning, weaving, and dyeing. In this context, the sustainability textile industry is a big challenge and contributes to serving a large segment of society. Also, textile wastes could be used as a raw material for added-value products. Herein, in this study, recycling of residues fabric was treated with antimicrobial nanocomposite to reach the best use of exhausts and obtain multifunction products of aesthetic via the technical design of the waste raw materials. Besides, solving the unemployment problem by opening fields for small industry projects capable of producing high-value textile artifacts, especially when treated against microbes, can be applied to home furnishings. The waste fabric was treated via green synthesis nanocomposite based on chitosan and in situ prepared ZnONPs and cross-linked with tannic acid. The prepared nanocomposite was characterized using physicochemical analysis including attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) and X-ray diffraction (XRD). Additionally, the nanocomposite and treated fabric topographical behavior were studied using scanning electron microscopy (SEM) attachment with energy dispersive X-ray analysis (EDX), and images were processed to evaluate the roughness structure. Additionally, high-resolution transmission electron microscopy (HR-TEM) and dynamic light scattering (DLS) were performed to ensure the size and stability of the nanocomposite. The obtained results affirmed the green synthesis of nanocomposite with a size around 130 nm, as well as the doped ZnONPs average size of 26 nm and treated waste fabric, performed a promising attraction between nanocomposite and fabric fibers. Moreover, the antimicrobial study observed excellent activity of nanocomposite against bacteria and unicellular fungi as well.

Design phase collaborative risk management factors: a case study of a green rating system in South Africa

PurposeWe explore the design risk factors and associated managerial practices driving collaborative risk management for design efficacy in green building projects. By illuminating project design risk as an important project risk category in its own right, the study contributes to our understanding of optimising design efficacies for collaborative project risk management.Design/methodology/approachThe study comprises exploratory interviews conducted with 27 industry project practitioners involved in the design and delivery/implementation of Green Star-certified building projects in South Africa.FindingsThe findings discursively highlight seven sources of design risk. We also identify seven specific collaborative risk management practices for design efficacy emerging from a consideration of how risk environments vary in the Green Star-certified projects, each with its own project design risk implications.Originality/valueThe study advances our understanding of how collaborations emerging from particular relational yet context-specific practices can be optimised to strengthen project risk management.

A comparative study of machine learning approaches for an accurate predictive modeling of solar energy generation

Solar energy prediction poses a challenging task that necessitates robust models and precise data to accurately forecast solar energy yield, especially in grid areas with high photovoltaic shares. Existing methods often rely on statistical or physical models, which have limitations in capturing the complex and non-linear relationships between weather variables and solar power generation. In this paper, we address this issue by comparing and evaluating different learning models, ranging from artificial neural networks (ANNs) and random forest models to long- and short-term memory (LSTM) networks, to predict the PV energy yield based on weather forecast data. A methodology has been developed to evaluate various models using real-world datasets from a large-scale industrial solar project, incorporating historical photovoltaic data, meteorological data, and solar irradiation data. The experimental results showed that the Random Forest Algorithm (RFR) consistently outperforms other algorithms, providing a mean absolute error (MAE) of 0.06 and a root mean square error (RMSE) of 0.15 when applied to historical meteorological datasets. The accuracy of the learning model was improved by combining meteorological data with a solar irradiation dataset to obtain an MAE of 0.03 % and an RMSE of 0.09 %. Validation analysis showed the proposed model is effective in both forecast accuracy and stability. The proposed methodology can provide valuable information to PV system operators, grid managers, and energy planners, facilitating the optimization of solar energy resources.

A megaton-scale industrial demonstration study on hydrothermal mineralization enabled silty waste upcycling

The continual large-scale urbanization and urban renewal in coastal cities of China have accumulated massive silty residue (SR) that may alter the coastal lines and always exerts high stresses to local environments. To meet China’s sustainable development policy, the need for green and high-efficient industrial treatments and reuse of SR is urgent. In this work, we may, for the first time, report a megaton-scale industrial project to upcycle low-quality SR and recycled aggregate (RA) to manufacture construction materials with hydrothermal mineralization (HM). In-situ pilot tests on five batches of SR-RA blocks were conducted. Results demonstrate that the produced blocks possess the compressive strengths of 11.4–15.8 MPa, densities of 1280–1430 kg/m3, porosities of 35–44%, CO2 emissions of 170.22–187.29 kg e-CO2/m3 and costs of 126.49–156.51 CNY/m3, comparable with or superior than the commercial blocks. The silica in SR could react with lime to produce tobermorite with stable pseudohexagonal plate under HM treatment, which improved the microstructure of the material. The findings validate the industrial practicability of upcycling low-quality SR and RA with HM for valuable construction block manufacture.

Reassessing Critical Success Factors for ERP Implementation in the Digital Era

This paper examines the recent evolution of Enterprise Resource Planning (ERP) systems and explores the critical success factors (CSFs) for project implementation in the digital age. Adopting a qualitative inductive approach, the article first reports on CSFs evident in relevant literature drawn from the past two decades. In the second research phase, interview feedback from nine industry project managers is analysed to identify the CSFs now considered of particular relevance in the digital era. The article concludes that many of the established CSFs remain relevant, but recent research suggests the deployment of digital technologies and the availability of the cloud for ERP operation will mean that CSFs will be re-formulated in new technology and business environments. CSFs related to cloud-based vs on-premise software operation, system configuration and functionality trade-offs, and the integration of digital technologies into ERP products, are likely to emerge in the digital era. Future studies could profitably focus on these largely unresearched aspects of ERP projects, to which this article makes a small contribution that may provide a useful point of reference for subsequent studies.

Enhancing effort estimation in global software development using a unique combination of Neuro Fuzzy Logic and Deep Learning Neural Networks (NFDLNN)

ABSTRACT Effective project planning and management in the global software development landscape relies on addressing major issues like cost estimation and effort allocation. Timely estimation of software development is a critical focus in software engineering research. With the industry increasingly relying on diverse teams worldwide, accurate estimation becomes vital. Software size serves as a common measure for costs and schedules, but advanced estimation methods consider various variables, such as project purpose, personnel expertise, time and efficiency constraints, and technology requirements. Estimating software costs involve significant financial and strategic commitments, making it crucial to address complexity and versatility related to cost drivers. To achieve enhanced accuracy and convergence, we employ the cuckoo algorithm in our proposed NFDLNN (Neuro Fuzzy Logic and Deep Learning Neural Networks) model. Through extensive validation with industrial project data, using Function Point Analysis as the algorithmic models, our NFA model demonstrates high accuracy in software cost approximation, outperforming existing methods insights of MRE of 3.33, BRE of 0.13, and PI of 74.48. Our research contributes to improved project planning and decision-making processes in global software development endeavours.

Determinants for the desirability of public-private partnership mode in infrastructure development

PurposeThis paper studies the determinants for the desirability of the public-private partnership (PPP) mode in infrastructure development.Design/methodology/approachThe author manually collects data on over 12,000 PPP projects in China, and regard the successful transition and abnormal termination as signals for the mode’s desirability and undesirability, respectively. Then, guided by relevant theories in the literature, the author investigates the impact of various project characteristics on the projects’ successful transition and abnormal termination.FindingsFirst, execution-stage projects in industries where government support is indispensable, or where quality improvement is more important than cost reduction, face higher likelihood of abnormal termination. But such negative effects are mitigated if state-owned enterprises (SOEs) participate in the social party. Second, the structure of social party matters. The participation by private firms in the social party increases the termination likelihood, while the decentralization of the social party decreases it. Third, pre-execution projects with government payment or subsidies are more likely to enter into the execution stage.Practical implicationsRegulations on participation by SOEs in PPPs, such as policy [2023 No. 115] announced by State Council, should take industrial heterogeneity into consideration.Originality/valueUsing a large sample, the author empirically tests the seminal PPP-related theories in the literature. The author also uncovers some unique stylized facts about PPPs in China, especially the impact of SOE participation in the social party on PPP survival.

Feasibility of Establishing and Re-operation of Industrial Projects in Iraq Through import-substitution strategy

The research idea originated from the significance of the industrial sector and its pivotal role in inducing structural and systemic changes at the national economic level. Given the numerous challenges the industrial sector faces in Iraq, many industrial projects have partially or entirely ceased operations. In contrast, state-owned industrial companies have become a burden on the government. Import substitution through manufacturing is considered one of the leading strategies and most vital industrial approaches that have historically catalyzed industrial growth and structural transformations in the economy. This has been evident in the development of countries that initially relied on primitive economic models centred around simple agriculture and the export of raw materials and transitioned into diversified economies with a significant industrial component, producing numerous high-quality and technologically advanced products. Based on this, the study aims to assess the compatibility of this strategy with the current Iraqi economic landscape. It seeks to shed light on inactive industrial projects and companies, exploring the feasibility of reactivating them or establishing new industrial ventures. Priority will be given to projects aligned with its objectives and goals. Additionally, the study aims to provide a forward-looking perspective on the state of the industry in Iraq's prospects, diagnose existing problems, and attempt to find solutions and remedies that can contribute to establishing a reliable industrial sector.

The development of fishery-photovoltaic complementary industry and the studies on its environmental, ecological and economic effects in China: A review

The fishery-photovoltaic complementary industry is an emerging industrial model in China that integrates aquaculture with the solar industry. This innovative model involves conducting aquaculture activities while installing photovoltaic modules on the water surface to harness solar energy for electricity generation. However, despite its rapid growth in China, this model lacks substantial scientific data support across various domains. Therefore, based on an analysis of relevant research literature, this study reviews the current development status, environmental and economic effects, as well as challenges faced by the fishery-photovoltaic complementary industry in China. The aim is to provide scientific references for promoting sustainable development within this sector. The findings reveal that existing fishery-photovoltaic complementary industry projects are primarily concentrated in the middle and lower reaches of the Yangtze River and Pearl River Basin. The geographical distribution of these projects is predominantly influenced by local aquaculture areas and available solar energy resources, with a greater impact observed from the former rather than the latter. During summer months when water is shaded by photovoltaic panels, a slight decrease in the average water quality parameters across cases was observed, such as a decrease of 0.2 units in pH, a decrease of 1.06 °C in water temperature, a decrease in dissolved oxygen levels of 0.8 mg/L, inorganic nitrogen content and total phosphorus concentration dropped by 0.08 mg/L and 0.02 mg/L respectively. Conversely, there is a moderate increase noted in total nitrogen and ammonia nitrogen levels. The conclusion of the effect on phytoplankton biomass is not uniform, but it will certainly reduce zooplankton biomass. The impact on the species diversity of the zooplankton community was minimal, and its direction, whether positive or negative, varied depending on the specific aquatic ecosystem. A certain degree of shade is advantageous for the cultivation of shade-loving fish. Through the strategic deployment of photovoltaic panels and the implementation of scientific stocking practices, it is possible to achieve sustained levels of fisheries production. This model also can reduce an average of 978.6 tons of CO2 emissions per megawatt per year through energy production, thus achieving the combined goals of energy conservation and emissions reduction, and ensuring the profitability of power generation. Additionally, compared with the land utilization area of 3.66 hm2 per megawatt of traditional ground-mounted photovoltaics, fishery-photovoltaic complementary only requires 1.64 hm2, which can significantly save land resources by utilizing water surfaces, which mitigates the conflict between land use for agriculture and renewable energy installations. At the same time, research also pointed out that the existence of fishery-photovoltaic complementary will inevitably have some negative impacts on bird communities. Economic analyses indicate that while initial infrastructure costs and long payback periods pose challenges, the overall economic feasibility is promising, especially with governmental support and technological advancements. However, several challenges need to be addressed for further development: these include difficulties associated with infrastructure construction and initial costs, long payback periods; insufficient experience and technical support; as well as a lack of research on ecological and environmental impacts - particularly an urgent need for comprehensive life cycle assessments encompassing both environmental and economic aspects. Future research should focus on life cycle assessments, improved PV technology integration, and optimized aquaculture practices.

EVALUATING AUTOMOTIVE SPICE® AS PROCESS REQUIREMENTS

AbstractSoftware and Systems engineering projects in the Automotive industry are often mandated to develop according to the Automotive SPICE® standard. Despite a highly qualified workforce, many projects or organizations fail to implement compliant processes. This paper reinterprets the Automotive SPICE® standard, viewing its base practices as process requirements. Using a set of quality criteria for requirements, the subsequent evaluation of base practices for quality results in an aggregate and individual analysis of the ASPICE base practices. The analyses reveal, amongst others, deficiencies in the aspects of singularity, unambiguity, and reasoning structure. The paper proposes a public, collaborative effort to enrich the requirements with purpose, detail, and structure.

Methodology for the design of a nanosatellite telecommunication system in S-Band based on Software for Digital Mission Engineering

Abstract A trend in the development of nanosatellite platforms for technology demonstration has increased in both private industry and academic projects. Communication link design plays a crucial role in the success of space missions, enabling efficient and reliable data transmission between satellites and ground stations. In this context, the use of advanced tools such as System Tool Kit (STK) has gained significant importance by enabling a comprehensive analysis of the technical and operational aspects of the communication link. In an effort to make the future design of the communications subsystem payload on a nanosatellite more efficient and accessible, this paper shows a methodology for the efficient use of STK to perform link analysis.

Collision Avoidance and Give Way of Heterogeneous and Variable-Sized Multiple Mobile Robots Based on Glued Nodes

Multiple mobile robot systems (MMRSs) play an important role in workshops, storage and other scenarios. A complex MMRS can contain heterogeneous robots, and even the robot sizes are not fixed, making it more difficult to avoid collisions. As a widely studied method, the zone-controlled method is not accurate enough for a system with heterogeneous and variable-sized robots, and it increases the difficulty of applying MMRS. Based on the concept of glued nodes, this paper proposes a more accurate calculation method than the zone-controlled method to avoid collisions among heterogeneous and variable-sized robots. In order to improve the efficiency of calculating glued nodes, this paper proposes a time-to-space method, which has a constant complexity after the system runs long enough. In addition to collision avoidance, this paper also studies the problem of giving way of idle robots. This paper proposes a method which can detect those idle robots blocking the working robots and plan paths for the idle robots to find avoidance nodes to give way to the working robots. Simulation experiments are carried out based on a real automated production line scenario, and the experimental results prove the effectiveness and efficiency of the proposed methods. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —In a complex MMRS, the size of different robots can be different, and even the size of a robot is different when loaded and unloaded. One of the motivations of this paper is to avoid collisions in such a complex MMRS. A collision avoidance method is proposed to avoid collisions among robots by allocating nodes in real time. At the same time, this paper also addresses the problem of idle robots blocking working robots. If an idle robot blocks some working robots, an avoidance node will be found for the idle robot to give way to the working robots. The methods proposed in this paper can be applied to the roadmap of any structure. This means that in a scenario, regardless of the structure of roadmap and the different sizes of robots, the methods can be applied directly. The methods have been applied to many practical industrial projects in warehousing, manufacturing and other scenarios, and greatly reduces the difficulty of applying MMRS. In future research, there is a need to improve the efficiency of the methods so that they can be applied to a large-scale system.

Team resilience in multiple project environments: What characteristics should be explored?

Purpose: This paper aims to explore how project team members' resilience differs based on industry type, project budget, company type, and gender. Design/methodology/approach: Using the conservation of resources theory, this study focuses on exploring the insight of the gathered data from the perspective of descriptive statistics. To achieve this objective, a descriptive analysis was conducted using purposive sampling and snowball techniques, gathering data from 349 respondents. The collected data was analyzed using IBM SPSS software version 25. Findings: The study's results indicate that male respondents are dominant, primarily working in the construction industry, while female respondents tend to work in other industry sectors. Moreover, male respondents exhibited higher resilience scores, but no significant difference in resilience was observed based on gender. However, resil-ience levels varied according to the industry sector. Respondents from industries other than the construction sector tended to display higher resilience. Research limitations/implications: Considering that the study finds only minor variations, businesses in the same industrial sector might think about implementing a practice benchmark. Examining businesses outside of these im-portant industries, however, may provide difficulties. Subsequent data-gathering endeavors may be broadened to encompass more industry sectors and subsequently scrutinized via case studies utilizing smaller samples from certain sectors. Originality/value: This study reveals that it is important to further expand and investigate these insights. Resources for team resilience, such as team confidence, a roadmap for teamwork, the ability to improvise as a team, and psychological safety for the team, can be added to future research. Furthermore, it is crucial to do quantitative research to look at how these elements show up in various industry sectors.

Mitigating delays and disputes in industrial construction projects: Lessons from a thermal power plant project in Turkey

Mitigating delays and disputes in industrial construction projects: Lessons from a thermal power plant project in Turkey