Industry Efforts Research Articles

Estimating personal electric vehicle demand and its adoption timeframe: A study on consumer perception in Indian metropolitan cities

India’s transition to electric vehicles has entered its second decade. The government has set a target of having EV sales accounting for 30 % of private cars and 80 % for two-wheelers by 2030. However, despite several efforts of government and industry, the penetration of electric vehicles till-date has not been as per the set targets. This study aims to estimate the end-user demand and adoption timeframe of electric 4-wheelers (e-4 W) and 2-wheelers (e-2 W) in India’s four large metropolitan areas. Binary logit choice models are developed based on a discrete choice experiment carried out by utilizing 2,400 face-to-face interview responses. In addition, ordered logit models are developed to assess the adoption timeframe of the EVs. The study results show a significant geographic variation in demand for e-4Ws and e-2Ws within India. This demand is also driven by vehicle attributes, demographics, infrastructural elements, and user attitudes. Existing vehicle owners are more likely to purchase an EV in the future, and are also likely to drive/ride it more. In addition, consumers who are young and wealthy, and living in homes with dedicated parking spaces are more likely to be early adopters of EVs. These findings would assist policymakers in designing a tailormade and phased EV implementation scheme in India.

Navigating the regulatory landscape: US environmental regulations pertaining to CO2 emissions

Amid growing apprehensions regarding climate change, regulatory frameworks governing carbon dioxide emissions play a crucial role in shaping industrial practices, energy policies, and environmental sustainability efforts. Through an examination of key regulatory bodies, such as the Environmental Protection Agency (EPA) and relevant legislation such as the Clean Air Act, this paper analyzes the intricate web of regulations governing CO2 emissions across various sectors. Additionally, the paper explores recent developments, including regulatory updates, policy shifts, and emerging trends, highlighting their implications for businesses, policymakers, and environmental advocates. By synthesizing complex regulatory information into a concise and accessible format, this paper aims to provide valuable insights for stakeholders navigating the dynamic landscape of US environmental regulations pertaining to CO2 emissions.

Predicting the stereoselectivity of chemical reactions by composite machine learning method.

Stereoselective reactions have played a vital role in the emergence of life, evolution, human biology, and medicine. However, for a long time, most industrial and academic efforts followed a trial-and-error approach for asymmetric synthesis in stereoselective reactions. In addition, most previous studies have been qualitatively focused on the influence of steric and electronic effects on stereoselective reactions. Therefore, quantitatively understanding the stereoselectivity of a given chemical reaction is extremely difficult. As proof of principle, this paper develops a novel composite machine learning method for quantitatively predicting the enantioselectivity representing the degree to which one enantiomer is preferentially produced from the reactions. Specifically, machine learning methods that are widely used in data analytics, including Random Forest, Support Vector Regression, and LASSO, are utilized. In addition, the Bayesian optimization and permutation importance tests are provided for an in-depth understanding of reactions and accurate prediction. Finally, the proposed composite method approximates the key features of the available reactions by using Gaussian mixture models, which provide suitable machine learning methods for new reactions. The case studies using the real stereoselective reactions show that the proposed method is effective and provides a solid foundation for further application to other chemical reactions.

Diving into progress: a review on current therapeutic advancements in spinal muscular atrophy

Spinal muscular atrophy (SMA) is an uncommon disorder associated with genes characterized by the gradual weakening and deterioration of muscles, often leading to substantial disability and premature mortality. Over the past decade, remarkable strides have been made in the field of SMA therapeutics, revolutionizing the landscape of patient care. One pivotal advancement is the development of gene-targeted therapies, such as nusinersen, onasemnogene abeparvovec and risdiplam which have demonstrated unprecedented efficacy in slowing disease progression. These therapies aim to address the root cause of SMA by targeting the survival motor neuron (SMN) gene, effectively restoring deficient SMN protein levels. The advent of these innovative approaches has transformed the prognosis for many SMA patients, offering a glimmer of hope where there was once limited therapeutic recourse. Furthermore, the emergence of small molecule compounds and RNA-targeting strategies has expanded the therapeutic arsenal against SMA. These novel interventions exhibit diverse mechanisms of action, including SMN protein stabilization and modulation of RNA splicing, showcasing the multifaceted nature of SMA treatment research. Collective efforts of pharmaceutical industries, research centers, and patient advocacy groups have played an important role in expediting the translation of scientific discoveries into visible clinical benefits. This review not only highlights the remarkable progress achieved in SMA therapeutics but also generates the ray of hope for the ongoing efforts required to enhance accessibility, optimize treatment strategies, rehabilitation (care and therapies) and ultimately pave the way for an improved quality of life for individuals affected by SMA.

Polyaniline-Based Cationic Porous Organic Polymers for Fast and Efficient Anion-Exchange-Driven Capture of Cr2O7 2.

Efficient treatment of wastewater contaminated with carcinogenic Cr(VI) has been a long-term challenge for both academic and industrial research efforts. Removal of Cr(VI) species by ion exchange is a relatively simple and efficient method, and its combination with highly tailorable nanomaterials is promising for the treatment of such wastewater. Here, we report a type of cationic porous organic polymer (POP), namely, PTPA-PIP, which can be prepared simply by converting the corresponding aromatic polyamine PTPA to its protonated form, thereby significantly increasing its hydrophilicity and ability to disperse homogeneously in water, crucial for application in water treatment. In addition to detailed characterization of the physicochemical properties of PTPA-PIP (including using Fourier transform infrared (FTIR), X-ray photoelectron spectroscopy (XPS), Brunauer-Emmett-Teller (BET), and solid-state NMR techniques), adsorption experiments demonstrate that PTPA-PIP removes low-concentration dichromate anions with very high performance, including excellent exchange capacity (maximum capacity of 230 mg Cr2O7 2-/g PTPA-PIP), ultrafast removal (initial adsorption rate of 83 mg g-1 min-1), excellent selectivity (∼10% loss of adsorption capacity in the presence of 40-fold concentration of competing anions), as well as superior reusability (reusable for at least 5 cycles without compromised performance). These results demonstrate that PTPA-PIP is an outstanding candidate for application in industrial settings for the effective removal of harmful Cr(VI) pollutants in wastewater.

Exploring the multidimensional challenges in integrating Design for Safety (DfS) in the Ghanaian construction industry

Purpose The uptake of Design for Safety (DfS) practices in developing countries like Ghana has been limited. This study aims to provide an in-depth understanding of the barriers across regulatory, organizational, cultural and educational dimensions that restrict DfS assimilation in the Ghanaian construction sector. Identifying the key impediments can inform policy initiatives and industry efforts to facilitate safer construction. Design/methodology/approach A postpositive philosophy underpinned the quantitative research. Multi-stage research was used. A comprehensive questionnaire survey was designed and given to six industry experts to assess clarity, relevance and effectiveness after a thorough literature review. In all, 164 professionals were reached to take part in the study using purposive sampling and consequently snowballing. “Variables” were ranked using mean score ranking and normalization techniques; exploratory factor analysis was then used to group variables into clusters. Findings Emergent findings revealed four distinct clusters of challenges; Design Process and Communication Challenges; Regulatory and Expertise Limitations; Planning and Education Constraints; and Attitudinal and Perception Barriers. These findings help identify targeted solutions to overcome barriers including developing robust regulatory frameworks, promoting collaboration among stakeholders and cultivating a positive safety culture. Originality/value This study provides new insights into the integration of DfS in the context of the developing construction industry in Ghana. This study expands the knowledge base to drive further research in enhancing construction safety in developing countries. Practical recommendations for overcoming these challenges are proposed.

Recent advances in micro-pixel light emitting diode technology

Display technology has developed rapidly in recent years, with III–V system-based micro-light-emitting diodes (μLEDs) attracting attention as a means to overcome the physical limitations of current display systems related to their lifetime, brightness, contrast ratio, response time, and pixel size. However, for μLED displays to be successfully commercialized, their technical shortcomings need to be addressed. This review comprehensively discusses important issues associated with μLEDs, including the use of the ABC model for interpreting their behavior, size-dependent degradation mechanisms, methods for improving their efficiency, novel epitaxial structures, the development of red μLEDs, advanced transfer techniques for production, and the detection and repair of defects. Finally, industrial efforts to commercialize μLED displays are summarized. This review thus provides important insights into the potential realization of next-generation display systems based on μLEDs.

“Oh Yes! Net-Zero”: Sociotechnical capabilities and regional innovation systems for British industrial decarbonization

Few sectors in the global economy need deep decarbonization as much as heavy industry, which is currently the largest and fastest growing source of global carbon emissions. Based on an original dataset of 111 expert interviews and 52 site visits, this paper asks: what sociotechnical pathways, capabilities, and regional innovation systems are emerging to support industrial decarbonization? It combines and applies insights from evolutionary economic geography and transitions studies, such as sociotechnical capabilities and learning, as well as spatial frameworks such as challenge-oriented regional innovation systems (CoRIS) and green industrial restructuring. It utilizes these collective concepts of pathways, capabilities and CoRIS to explore the organizational and technological, individual, and systems level dimensions of industrial decarbonization efforts ongoing across Great Britain. We find that within industrial net-zero clusters, spatial and technological proximities are being effectively leveraged, especially through new forms of networking, collaboration, and partnerships. CoRIS provides the basis for greater reflection on perennial transitions issues, both within and across clusters, related to incumbency and innovation, in addition to spotlighting emergent issues such as light versus deep green restructuring and incremental versus transformative change. In simpler terms, industrial decarbonization unfolds as a multi-scalar process. Industrial decarbonization exhibits both incremental and transformative patterns of change. Industrial decarbonization lastly involves dynamic processes that coevolve across a spectrum of sociotechnical attributes.

How do consumers with different food neophobia levels react to health and environmental information? A case study on legume‐based formulations

AbstractThe global environmental changes require the development of new food formulations with sustainable ingredients. In this context, legumes could be used to enrich foods with beneficial consequences both on human health and sustainability of the agri‐food system. The aim was to evaluate the liking of a whole corn‐based formulation including chickpea or red lentil flour with or without providing health and environmental information about legumes. The effect of the conveyed information in subjects with different food neophobia (FN) level as well as the association between FN and different sustainability dimensions were also investigated. A 100% whole‐corn sample and two samples added with 20% of chickpea or red lentil flour were tested by 127 consumers in blind, expected, and real conditions. Subjects completed questionnaires about FN, sustainable behavior, perceived environmental impact of food products, beliefs, and attitudes toward sustainable food. Legume‐based products were equally liked as the control sample indicating that these food ingredients are promising for the enrichment of polenta samples. The information increased consumers' hedonic expectations. However, incomplete assimilation was found for samples with legumes. When the effect of information was assessed as a function of FN level, a complete assimilation for subjects with low (chickpea sample) and medium (red lentil sample) FN score was found, while no significant effect was seen for subjects with high FN score. A significant negative association was found between FN and sustainability commitment.Practical ApplicationThe results of the present study demonstrate that the development of sustainable food formulations using legumes is promising and that conveying health and environmental sustainability information contribute to increase consumer acceptance. However, consumers with high levels of FN were insensitive to information and were also those with low interest in sustainability issues. As a practical application, personalized communication strategies should be developed to reach different consumers targets when specific innovations are launched on the market alongside with industry efforts in developing marketing initiatives raising consumers awareness about health and environmental aspects.

Experimental investigation on the potential of passive prechambers for use in 2S engines

Design improvement of Internal Combustion Engines (ICEs) is required by the continuous update of European exhaust emission standards and vehicle registration protocols. This has pushed research and industry efforts towards the development of Low Temperature Combustion (LTC) systems. Among various LTC technologies, the so called “jet ignition” is claimed to be well-suited for light engines, since it provides a more uniform and rapid combustion while ensuring the mixture ignition process. In this context, the adoption of prechambers was found well-suited for two-stroke engines, for which low-pressure direct injection technologies have been developed in the last decade to reduce the fuel short circuit phenomenon. The present paper experimentally investigates the use of different passive combustion prechambers in a Low-Pressure Direct Injection (LPDI) 2-stroke engine, with the main purpose to understand the relationship between prechamber geometrical parameters and engine performance. A 50-cc single cylinder LPDI motorcycle engine is chosen as the test case and it is re-arranged to run in jet ignition mode. The experimental analysis focuses on the evaluation of benefits provided by jet ignition combustion compared to the baseline LPDI propulsion unit at different engine operating points. Design criteria for prechambers development and the tuning process of engine combustion parameters (such as start of injection, ignition time and throttle valve opening) are described in detail. The results of experimental activity are finally shown and critically discussed, highlighting advantages and disadvantages of this application in terms of engine performance, efficiency and cycle-to-cycle variation.

The trace amine-associated receptor 1 agonists - non-dopaminergic antipsychotics or covert modulators of D2 receptors?

A major effort of the pharmaceutical industry has been to identify and market drug treatments that are effective in ameliorating the symptoms of psychotic illness but without the limitations of the current treatments acting at dopamine D2 receptors. These limitations include the induction of a range of adverse effects, the inadequate treatment response of a substantial proportion of people with schizophrenia, and the generally poor response to negative and cognitive features of the disease. Recently introduced drug treatments have gone some way to avoiding the first of these, with a reduced propensity for weight gain, cardiovascular risk and extrapyramidal motor effects. Despite claims of some small improvements in negative symptoms, these drugs have not demonstrated substantial increases in efficacy. Of the drugs currently in development as antipsychotic agents, several are misleadingly described as having novel 'non-dopaminergic' mechanisms that may offer improvements in addressing the limitations of adverse effects and efficacy. It will be argued, using the trace amine-associated receptor 1 agonist as an example, that several of these new drugs still act primarily through modulation of dopaminergic neurotransmission and, in not addressing the primary pathology of schizophrenia, are therefore unlikely to have the much-needed improvements in efficacy required to address the unmet need associated with resistance to current treatments.

Strength Properties of Blended Cement Mortar with Metakaolin and Rice Husk Ash

This study investigates the feasibility of using rice husk ash (RHA) and metakaolin as substitutes for Ordinary Portland Cement (OPC) in mortar production to reduce greenhouse gas emissions associated with construction. The study employs MM3 grade mortar, with RHA replacing cement at varying percentages (0%, 5%, 10%, and 15%), while metakaolin consistently substitutes 10% of the cement. Compressive strength tests are conducted on specimens cured for 7, 14, and 28 days to assess performance. The study utilizes OPC 53-grade cement with a water-cement ratio of 0.4. In total, four mortar mixes are prepared, and each mix comprises nine specimens, totaling 45 specimens. Initially, conventional mortar is evaluated for its physical and mechanical properties. The study aims to contribute to ongoing efforts in the construction industry to explore sustainable alternatives to conventional materials, such as RHA and metakaolin, while ensuring the requisite strength properties of mortar are maintained. Key Words: Rice husk ash, metakaolin, cement, sand, mortar and compressive strength

Leading the post-industrial revolution? Policy windows, issue linkage and decarbonization dynamics in the UK’s net-zero strategy (2010–2022)

Abstract Industrial decarbonization and the net-zero climate strategy has arisen as one of the most important policy challenges of the modern era. But how do industrial decarbonization policy efforts link with other issues? The UK claims to be the first major economy in the world to posit a net-zero target. In this paper, drawn from an original qualitative dataset involving expert interviews (N = 46), site visits (N = 20), and a review of the literature, we explore ongoing policy windows and efforts to decarbonize both the Humber and Merseyside. These regions have aggressive implementation plans in place for the deployment of net-zero infrastructure, with Zero Carbon Humber and HyNet seeking billions of dollars of investment to build green and blue hydrogen facilities coupled with carbon storage networks. These two clusters are leading national net-zero ambitions, with actual, enforceable timetables to achieve decarbonization. Investigating the unfolding efforts being undertaken by these two regions to decarbonize industry offers insight into the “green gold rush” and nascent business opportunities in the so-called carbon economy, including large-scale investment of capital into the policies nominally designed to tackle climate change. Through the identification of 24 different issues linked to decarbonization, the paper also offers more conceptual depth into the interplay between policy windows and issue linkage, which coevolve and shape each other as net-zero ambitions solidify.

Innovation Strategies and Competitive Advantage of Ceramic Manufacturers in Kenya

Manufacturing firms are crucial for Kenya's economic growth and industrialization efforts aligned with Vision 2030 objectives. However, recent trends show a decline in competitive advantage for these firms, reflected in decreasing market share, customer loyalty, and sales growth. To address this, firms have adopted innovative strategies like process, product, and technology innovation to enhance their competitive edge. The decline in competitive advantage poses risks to profitability, market position, and long-term sustainability, underscoring the importance of investigating the impact of innovation strategies on the competitive advantage of ceramic manufacturers in Kenya. Therefore, the purpose of the study is to evaluate the relationship between innovation strategies and the competitive advantage of ceramic manufacturers in Kenya. The purpose of the study was to ascertain how Kenyan ceramic producers' competitive advantage was impacted by innovation in technology, products, and processes. The study used a desktop research approach, and theme analysis was used to examine the data. The study discovered that Kenyan ceramic producers' competitive edge stems from process innovation. Furthermore, the results showed that Kenyan ceramic producers' competitive advantage stems from product innovation. The results also showed the impact of technological innovation on Kenyan ceramic producers' competitive edge. The study concluded that Kenyan ceramic producers had a competitive edge due to process, product, and technological innovation. Manufacturers of ceramics must take a whole-hearted commitment to innovation, covering all facets such as procedures, goods, and technology.

Estimating adaptation effort in industry 4.0-enabled systems: Introducing two complexity indices with an evolvable network graph approach

One of the key aims of Industry 4.0 is to create more responsive systems. Responsiveness enables coping with new market requirements or introducing new products, as demonstrated by the COVID-19 challenges. However, there are currently no effective methods for measuring the responsiveness or reconfigurability of a system, or for quantifying the effort required to adapt it from one state to another. Adapting a production cell from its current state to a new adapted state requires a significant amount of information about dismantling, reintegrating, and handling physical equipment, as well as updating the software controller. Practitioners often only consider adaptation options for simple process parametrization or at the end of a system's life cycle, overlooking many potential adaptation opportunities. This paper proposes an evolvable network graph approach for supporting reconfiguration decisions by estimating the effort required to adapt the physical structure. Two complexity indexes have been developed to quantify the adaptation activities. An estimation algorithm infers the effort from the difference in the adaptation graphs that represent alternative options. The approach is illustrated in a laboratory-scale cell and applied in two industrial-sized cells, quantifying adaptation times of approximately 58, 7, and 122 h, respectively. This is equivalent to £3129.6, £356.04, and £6118.8, utilizing average hourly rates for system integrators and equipment handlers. The results show that the approach can effectively quantify the adaptation effort for different equipment sizes and connections, estimating the adaptation cost and time from the graph change quickly at around a millisecond and with minimal computational resources.

Comprehensive analysis of dynamic topology sensor linkage for the internet of things

In today’s developing IoT world, wireless sensor interactions are critical. To ensure full system IP compatibility, industry efforts are focused on standardizing the WSN protocol suite and enabling the second generation of IoT devices to be produced. As a result of their robust communications and conformance to less verbose WSN features such as sleep cycles required to keep end nodes’ total energy consumption low, the WSN protocols are strong contenders for use as a highly useable implementation layer for the IoT. Existing smart systems make use of system assets for critical IoT functions. Compared to a wired configuration, wireless sensors are easier to install and provide more device flexibility. As sensor technology advances, WSNs will become a critical component of the IoT and an essential tool for achieving the IoT paradigm’s goal. It’s also crucial to think about whether or not a WSN’s sensors should be fully linked into the IoT’s. For WSNs, a multi-objective optimization technique for selecting the most energy-efficient CH is described. The CHs for each lattice were first selected using a candidate CH selection method. Energy waste and data redundancy were also decreased by using multi-hop networking. An inventive new method has also been devised to ensure perfect implementation. The Evolutionary Algorithm (EA) model and optimization techniques used in this work provided an energy-efficient Machine Learning (ML) strategy for selecting WSN CH. First, the CH of each lattice was calculated using a candidate CH selection method. According to the results of the simulation, the suggested model’s performance is superior to traditional approaches in terms of network lifespan, energy efficiency, and reduced consumption.

Heat integration, simultaneous structure and parameter optimisation, and techno-economic evaluation of waste heat recovery systems for petrochemical industry

Energy conservation in the petrochemical sector holds the key to its financial viability. The pervasive application of Heat Exchanger Networks (HEN) exemplifies the industry's efforts in heat recovery. Yet, despite its widespread adoption, an alarming quantum of low-grade heat remains squandered, underscoring the potential for augmenting energy savings through more effective utilization of this heat. Recognizing the pivotal role of the synergistic interaction between the process and the heat recovery system in maximizing energy retrieval, an innovative approach is proposed. This methodology initially entailed the development of a process model and an enhanced heat recovery system, the latter embodying the integration of an organic Rankine cycle (ORC) with HEN. Subsequently, a strategic diagnostic was proposed to incorporate these sub-systems into a cohesive, optimisation framework. Following this, an array of energy, exergy, and economic analyses were conducted to appraise the system's performance. The findings suggest a considerable improvement in heat recovery and an amplification in ORC efficiency from a mere 7.64%–11.38%. The enhanced heat recovery further translated into a reduced need for cold utility, thereby minimizing cooler deployment. Given the substantial exergy destruction associated with coolers, their lesser usage bolstered the system's exergy efficiency. Moreover, the optimised ORC manifested in heightened net power generation, consequently elevating electricity revenues. Despite a nominal surge in equipment costs, the aggregate profit witnessed a substantial hike from 165.19 M$/year to 178.79 M$/year. The proposed system substanitally improved thermodynamic and economic performance. This study offers valuable guidance for the design and operation of petrochemical industries, serving as a roadmap to energy conservation and enhanced profitability.

Efficient annotation reduction with active learning for computer vision-based Retail Product Recognition

The retail industry encounters huge obstacles with computer vision (CV) technology due to frequent model retraining with changing products and time-consuming, costly data annotation. Previous research in this field has been primarily focused on optimizing model performance rather than minimizing annotation effort. Therefore, the main idea of this paper is to evaluate active learning as a method to minimize annotation effort in the retail industry. The MVTEC Densely Segmented Supermarket dataset is used to evaluate various active learning methods such as the Least Confident, Entropy and Cost-Effective Active Learning (CEAL) along with Mask R-CNN model. The results demonstrate that annotating only 20.83-\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$-$$\\end{document}24.34% of the data achieves 95% of the full dataset’s performance. When training, out-of-sample data share similar characteristics, the Least Confident and CEAL methods reduce annotation requirements by 7.7-\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$-$$\\end{document}15.7% while maintaining 95% and 97% of the full dataset’s performance. However, the Entropy method under-performs compared to the random selection baseline. Ultimately, none of the methods show a clear advantage when the data characteristics differ between training and out-of-sample data. Finally, the proposed active learning methods on an industry-specific retail dataset remarkably propels the development of highly efficient and cost-effective CV solutions meticulously tailored for the retail industry.

Effect of Heat Treatments on Microstructure and Mechanical Properties of Fe-Mn-Ni-Al-Gd Shape Memory Alloy

There are significant scientific and industrial efforts to develop and optimize Iron-based shape memory alloys (SMA) such as FeMnNiAl for cost-sensitive applications. This alloy system shows shape memory and superelastic properties across a large temperature range. However, many studies have pointed out the need for rather complex thermo-mechanical treatments for the optimization of the SMA properties. In addition, works considering the effects of alloying on the development of microstructures that are more conducive to pseudo-elasticity in this system remain limited. Hence, systematic studies aiming at the investigation of the microstructural evolution of the FeMnNiAl(Gd) system are of great interest. In this study, solution heat treatment is done to tune the microstructure for optimum mechanical properties. The effect of phase distribution on mechanical properties is investigated at different heat treatments. Whereas cyclic heat treatment induced abnormal grain growth (AGG) in all samples, so large grains were obtained. The phase variation and elemental composition are analyzed by X-ray diffraction and Energy Dispersive Spectroscopy, respectively. The microstructure and phase distribution are observed using Scanning Electron Microscope and then related to the microhardness results. The microstructure has a good correlation with mechanical properties where the fine distribution of phases results in a higher hardness number.

The Urbanization Process in Nha Trang City (Khanh Hoa Province,Vietnam) From 1989 To 1999

In 1989, Khanh Hoa province underwent restructuring to facilitate the full utilization of the region's potential. Despite initial hurdles during the renovation period, the urbanization of Nha Trang city progressed dynamically, spurred by the positive effects of renovation policies, industrialization, and modernization efforts. Transitioning from a type III urban area, by 1999, Nha Trang had advanced to a type II urban area. Industries and services took precedence in the economic landscape, while significant investments were made to upgrade urban infrastructure. Consequently, population density surged, accompanied by gradual enhancements in both the physical and psychological well-being of the populace. Drawing upon information provided by the Khanh Hoa Provincial Statistics Office, the Party Committee of Nha Trang city, and neighborhood administrations, this article employs historical and logical approaches intricately intertwined with analytical, synthetic, and comparative methods. Through this comprehensive framework, the aim is to elucidate the accomplishments and challenges encountered by Nha Trang city throughout its urbanization journey from 1989 to 1999 across various domains.