Sustainable Development Process Research Articles

Enhancing the Ecosystem of Central Areas in European Metropolises: A Project for Rome

The paper presents the results of a third-party research project defining the process of redevelopment and social and environmental regeneration along the historic urban axis of Via Nazionale and Corso Vittorio Emanuele II in Rome. The site is affected by the construction of the new tram line connecting Termini Station to the Vatican City. The study proposes an approach to the design of public spaces that, starting by inhibiting traffic from rubber-tired vehicles and private cars and the application of environmental mitigation strategies, allows to reduce pollutant emissions, enhance the cultural heritage along the urban axis, and revitalise cultural, social, and commercial activities, thus triggering a virtuous process of sustainable growth and development.

A Multi-Scale Evaluation Model of Sustainable Development Goal 11.7 for Problem-Solving at Different Levels

Sustainable Development Goal 11.7 (SDG 11.7) aims to promote the improvement of urban public spaces. However, the localization process of SDG 11.7 mainly relies on a bottom-up problem-solving approach, which fails to fully encompass the connotation of SDG 11.7. Additionally, existing evaluations primarily focus on a single scale, neglecting the impact of scale issues. These limitations can lead to imbalanced development or misallocation of responsibilities when guiding governments at different levels in promoting the sustainable development of public spaces. Therefore, this article introduces a multi-scale assessment model of SDG 11.7. It employs a top-down problem-solving approach to construct a sustainable development indicator framework, setting appropriate sustainable development indicators for various levels of government based on the connotation of SDG 11.7, and generates city-scale results by integrating three scales: apartment complexes, street blocks, and counties. Testing this model in Xi’an, China, revealed that it adequately captures four key aspects of SDG 11.7—safety, inclusiveness, accessibility, and greenness—through 11 indicators. The evaluation outcomes at the apartment complex, street block, and county levels effectively guide future development directions for various levels of government. Ultimately, the synthesis of these scales reveals the spatial pattern of SDG 11.7 at the city scale and identifies focal areas for development. Overall, this exploratory model demonstrates high accuracy and robustness, providing a comprehensive understanding of the essence of SDG 11.7. It also alleviates challenges posed by scale issues, offering decision support for monitoring SDG 11.7 across different levels of government in Chinese cities and promoting the process of sustainable development.

Study on the Quality of Environmental Accounting Information Disclosure of Alibaba Group

Abstract: This paper aims to study and analyze the quality of environmental accounting information disclosure of Alibaba Group, a leading global integrated business giant. Since its establishment in 1999, Alibaba has not only achieved tremendous success in the business field but also shown a positive attitude towards environmental protection and social responsibility. This study examines Alibaba's ESG reports to explore its practices and disclosures concerning environmental responsibility and sustainable development. Using content quality analysis, an evaluation system comprising adequacy, significance, and quantification dimensions was developed to systematically assess Alibaba's environmental accounting information disclosure. Results indicate that while there have been improvements in the adequacy and significance of the information disclosed, significant gaps remain in quantification. Based on the findings, this paper proposes several recommendations aimed at further enhancing the quality of Alibaba's environmental accounting information disclosure, thereby boosting corporate transparency and fulfilling social responsibilities to foster sustainable development. This research not only offers strategies for improving Alibaba Group's environmental accounting information disclosure but also provides practical guidance for other corporations in terms of environmental protection and social responsibility fulfillment. Through an in-depth analysis of the quality of environmental accounting information disclosure, this study hopes to encourage corporations to better recognize the importance of environmental responsibilities and adopt effective measures to jointly propel the global sustainable development process.

The Stability Challenge of Furanic Platform Chemicals in Acidic and Basic Conditions.

The transition toward renewable resources is pivotal for the sustainability of the chemical industry, making the exploration of biobased furanic platform chemicals derived from plant biomass of paramount importance. These compounds, promising alternatives to petroleum-derived aromatics, face challenges in terms of stability under synthetic conditions, limiting their practical application in the fuel, chemical, and pharmaceutical sectors. Our study presents a comprehensive evaluation of the stability of furan derivatives in various solvents and under different conditions, addressing the significant challenge of their instability. Through systematic experiments involving GC‒MS, NMR, FT‒IR and SEM analyses, we identified key degradation pathways and conditions that either promote stability or lead to undesirable degradation products. These findings demonstrate the strong stabilizing effect of polar aprotic solvents, especially DMF, and reveal the dependence of furan stability on solvent and additive type. This research opens new avenues in the utilization of renewable furans by providing critical insights into their behavior under synthetic conditions, significantly impacting the development of sustainable materials and processes. The broad appeal of this study lies in its potential to guide the selection of conditions for the efficient and sustainable synthesis of furan-based chemicals, marking a significant advance in green chemistry and materials science.

Widening the stimuli-responsiveness of aqueous biphasic systems by changing the ionic liquid cation basicity.

Herein we demonstrate the formation of new stimuli-responsive aqueous biphasic systems (ABS), able to respond simultaneously to temperature and pH, or just to one stimulus, therefore allowing the design of more sustainable separation processes. This dual behavior is achieved with ABS formed by mono or dicationic protic ionic liquids as phase-forming components, being defined by the ionic liquid cation chemical structure or its basicity. While ABS comprising monocationic ionic liquids only respond to the effect of temperature, systems comprising dicationic ionic liquids are simultaneously affected by both temperature and pH variations. Dicationic ionic liquids are here identified as the key to unlock a double response to stimuli, which is due to the presence of two pKa values afforded by the cation. The reported findings contribute to increase the customizability of double stimuli-responsive ABS based on ionic liquids, whose development was up to date limited to ionic liquids bearing pH-responsive anions, opening the door towards the development of more sustainable separation processes.

Selective Photocatalytic Benzene Oxidation Using Iron‐Carbon Nitride Fragments Functionalized with Cyamelurate‐Like Groups

Carbon nitrides have emerged as promising supports for catalytically active metals in various chemical reactions. Among these, the selective oxidation of benzene to phenol stands out as particularly challenging within the chemical industry due to its traditionally low yields and complex reaction pathways. In our current investigation, we have focused on the synthesis of ionic carbon nitride fragments via a straightforward alkaline hydrolysis method. These fragments demonstrate a remarkable ability to stabilize iron cations within the carbon nitride structure (Frag‐Fe), resulting in a highly efficient photocatalyst for benzene oxidation. Employing hydrogen peroxide as the oxidant in a single‐step reaction, we achieved an impressive 47% yield of phenol using Frag‐Fe at 12 hours, with negligible production of CO2 as a byproduct. This compelling outcome underscores the effectiveness of our alkaline synthesis approach in generating carbon nitride‐based photocatalysts with exceptional activity for C‐H oxidation reactions. Our findings not only contribute to the advancement of carbon nitride‐based catalysis, but also hold significant promise for the development of more sustainable and efficient chemical processes in the future.

Sustainable development of the Republic of Bashkortostan of the Russian Federation: current state and prospects

The issues and prospects of sustainable development of the Republic of Bashkortostan with a focus on innovation aspects have been considered in order to develop recommendations to ensure the long-term progress of the region. The research methodology is based on the analysis and comparison of economic, social, and environmental factors of sustainable development, assessment of the role of innovation in each sphere, study of successes and experience of other constituent entities of the Russian Federation and foreign countries, as well as on the proposals for creating regional centers for assessing and monitoring sustainable development that in their activities will be focused on comprehensive research in regional socio-economic systems, considering the innovation component. The main spheres and components of ensuring sustainable development of the region have been defined and presented. The main study results are: identification of key aspects of sustainable development of the Republic of Bashkortostan; identification of issues and prospects in developing the economy and social and environmental spheres; analysis of the role of innovation in ensuring sustainable development; recommendations development for creating regional centers for assessing and monitoring sustainable development. Sustainable development of the territory is one of the main strategic objectives of the constituent entity. In order to achieve it, it is necessary to continue the work, as well as to increase attention to innovations, education and management systems. The centers creation can contribute to the system analysis and assessment of sustainable development processes, as well as the development of recommendations and strategies to improve the economic, social, and environmental condition of the territory.

Preface: 13th Ranshofener Leichtmetalltage

Abstract What strategies are available to minimize resource consumption in the light metal industry through recycling and energy efficiency? How can lightweight design make mobility more sustainable? And what role will artificial intelligence play in future processes in the metal processing industry? These and other questions are addressed at the 13th Ranshofener Leichtmetalltage 2024, which take place on the 26th–27th of September 2024 at the Hotel Gut Brandlhof in Saalfelden, Austria, and are organized in accordance with the criteria of the Austrian Ecolabel for Green Events. Under the guiding theme of “Light Metals Innovations for Environmental and Economic Sustainability”, this year’s conference offers an exciting program in three sessions “Digitalization in the Context of Circularity”, “Sustainable Process Development” and “Innovative Light Metals and their Characterization”. The focus is on decarbonization and digitalization in process and material development as well as the material characterization of light metals. A balanced spectrum of international presentations from universities, RTOs and industry provides participants with an up-to-date overview of the latest scientific findings and successful light metal applications. The 13th Ranshofener Leichtmetalltage 2024 are thus clearly focused on decarbonization and digitalization – even in times of diverse challenges. The first session, “Digitalization in the Context of Circularity”, highlights best-practice examples from the aluminium industry, the balance between sustainability and performance in metal processing and the implementation of complex geometries using wire-based additive manufacturing. The second session, “Sustainable Process Development”, is dedicated to the decarbonization and reduced material consumption of industrial processes, for example through GigaCasting, or the use of innovative recycling technologies. The third session, “Innovative Light Metals and their Characterization”, addresses forward-looking topics such as the development of special aluminium alloys for additive manufacturing, the use of old car scrap for innovative alloys and the decarbonization of the magnesium industry. The conference proceedings contain scientific contributions to the conference. We would like to thank all the authors for their high-quality work and the participants of the 13th Ranshofener Leichtmetalltage 2024 for their interest. We wish you stimulating reading and creative impulses! List of Scientific committee, Organizing committee are available in this Pdf.

Urban eco-efficiency of China: Spatial evolution, network characteristics, and influencing factors

Urban eco-efficiency (EE) refers to the ability of a city to balance economic growth with environmental protection through the optimal use of resources and environmental management, reflecting the city’s performance in sustainable development. Quantitative EE analysis is a crucial evaluation criterion for measuring the process of sustainable development (SD). To assess the current state of sustainable development in China, this study employs the slacks-based super efficiency model (Super-SBM) to measure the the urban eco-efficiency in China (CUEE) of 284 cities. The study utilizes Kernel Density Estimation (KDE) and Spatial Autocorrelation Analysis (SAA) to investigate the fundamental patterns of CUEE in terms of inter-city differences and relationships. Complex Network Analysis (CNA) and Link Prediction methods are applied to examine the characteristics and future trends of the CUEE network. Additionally, Geodetector and Geographically Weighted Regression (GWR) are used to analyze the influencing factors of CUEE. The findings are as follows: Overall CUEE is relatively low but shows a steady increase. The spatial association network of CUEE is becoming more complex, with increasing association strengths. The Chengdu-Chongqing Economic Circle (CCEC) is expected to further enhance its spatial association strength and may emerge as a new core area. The effectiveness of the interactions among selected factors is greater than that of individual factors. Degree centrality (X1) is identified as a core explanatory factor influencing CUEE, showing a positive correlation with CUEE. Scientific expenditure (X5) is also positively correlated with CUEE. Local fiscal budget expenditure (X3), industrial output value of foreign-invested enterprises (X7), and total cargo transportation volume (X9) are negatively correlated with CUEE. The analytical framework and research conclusions of this study offer valuable insights into the development of urban ecological efficiency in China and provide constructive recommendations for promoting sustainable urban development.

Sustainable Chemical Modification of Natural Polysaccharides: Mechanochemical, Solvent-Free Conjugation of Pectins and Hyaluronic Acid Promoted by Microwave Radiations.

The modern chemistry has the main focus of saving resources and developing synthetic strategies characterized by intrinsic efficiency, ease and safety in operation, short reaction time, reduced energy, and waste. Natural polysaccharides are largely distributed in plant/animal cells; in other words, they are often provided by renewable sources. This characteristic makes them suitable compounds to be investigated for their employment as biodegradable material. In addition, natural polysaccharides have been proven to have a wide range of applications, and this prompted researchers to investigate their chemical modifications in order to modulate their properties. Herein we discuss the development of conjugation strategies of some polysaccharides with natural substrates and the effects of the structural modification on their bioactivities. Finally, this work intends to provide suggestions and perspectives on the development of safe and sustainable synthetic processes on polysaccharides.

The intersection of economic growth and environmental sustainability in China: Pathways to achieving SDG

This study explores the intricate relationship between economic development and ecological degradation in China to find ways to achieve the set goals of sustainable development within the framework of the SDGs. Fueled by the pursuit of sustainable development alongside economic growth, this study includes dimensions like carbon footprint, air and water pollution, and resource consumption in thirty-three provinces of China for the period of 2005–2015.Based on economic, environmental, and political perspectives, the existing research compares one policy measure the Chinese government has adopted to promote sustainable environmental development while continuing economic growth. This study, therefore, highlights the trade-offs and co-benefits between environmental conservation and development, based on an evaluation of large datasets and a review of literature. In analyzing the key findings, the paper notes significant progress and shortcomings in achieving the set Sustainable Development Goals. The findings indicate that sustainable clean water investments synergize with the protection of land-based ecosystems and climate action plans. Therefore, these findings enhance the understanding of China's sustainable development process, providing relevant knowledge to practitioners, policymakers, and scholars to tackle similar issues worldwide. The study demonstrates the need for policy coherence and intervention measures to align economic development with environmental conservation, contributing to the discourse on sustainable development.

Bijel-based mesophotoreactor with integrated carbon nitride for continuous-flow photocatalysis

The integration of continuous-flow technologies with heterogeneous photocatalysis has recently emerged as a promising strategy for the development of sustainable processes. Although conventional packed bed reactors have been extensively utilized in industrial catalytic applications, they face challenges related to energy transfer in the photocatalytic systems. This study presents an innovative approach to address this issue by integrating heterogeneous photocatalysts with an organic polymer, leading to the fabrication of a mesophotoreactor featuring a bijel-based structural configuration. This novel strategy involves hybridizing polypentadecalactone and in situ confining of carbon nitride in a bicontinuous porous mesoarchitecture. The structural and physicochemical properties of the resulting catalytic composite material are evaluated through an array of characterization methods, affirming the successful integration of carbon nitride within the overall structure. The unique bicontinuous porous architecture of the composite and its suitability for industrial applications is verified, as exemplified by its exceptional efficiency in the photodegradation of methylene blue (>99 %) under flow conditions and remarkable stability up to three reaction cycles. A mathematical model is developed to describe continuous photocatalytic processes occurring in the novel tubular mesophotoreactor, with a specific focus on the degradation of the methylene blue dye. This model is successfully validated, leading to results in agreement with the experimental measurements. Additionally, fluid dynamics simulations demonstrate that the mesophotoreactor design allows for the effective diffusion of light through its channels, resulting in higher irradiation levels compared to conventional systems such as packed bed reactors. The innovative design of the catalytic reactor presented in this work offers a versatile and efficient alternative to the conventional heterogeneous systems, significantly broadening the range of applications for photocatalytic processes.

Identifying influencing factors and characterizing key issues in urban sustainable development capacity through machine learning

In response to the United Nations Sustainable Development Goals and China’s “Dual Carbon” Goals (DCGs means the goals of “Carbon Peak and carbon neutrality”), this paper from the perspective of the construction of China’s Innovation Demonstration Zones for Sustainable Development Agenda (IDZSDAs), combines carbon emission-related metrics to construct a comprehensive assessment system for Urban Sustainable Development Capacity (USDC). After obtaining USDC assessment results through the assessment system, an approach combining Least Absolute Shrinkage and Selection Operator (LASSO) regression and Random Forest (RF) based on machine learning is proposed for identifying influencing factors and characterizing key issues. Combining Coupling Coordination Degree (CCD) analysis, the study further summarizes the systemic patterns and future directions of urban sustainable development. A case study on the IDZSDAs from 2015 to 2022 reveals that: (1) the combined identification method based on machine learning and CCD models effectively quantifies influencing factors and key issues in the urban sustainable development process; (2) the correspondence between influencing factors and key subsystems identified by the LASSO-RF combination model is generally consistent with the development situations in various cities; and (3) the machine learning-based combined recognition method is scalable and dynamic. It enables decision-makers to accurately identify influencing factors and characterize key issues based on actual urban development needs.

Constructing a standard system of city sustainable development assessment technology based on the SDGs

Given the rapid development of China’s new urbanization, cities with different locations and varying functional positioning, resource endowments, and development stages have insufficient scientific and applicable technical tools for implementing the United Nations Sustainable Development Goals (SDGs). City managers and policymakers must urgently establish SDG benchmarks to diagnose city development. Moreover, successful experiences from similar cities regarding sustainable development and self-improvement must be learned from to promote diversified, sustainable development across the country. Furthermore, emerging technologies such as artificial intelligence, the Internet of Things, big data and 5G are widely used in smart cities. Therefore, there is a growing need for “knowledge-based, personalized and intelligent” technologies to support monitoring, evaluation, and decision-making processes facilitating sustainable development in cities. This paper uses standardization as the theoretical support and technical basis. This approach can help clarify the sustainable development processes in China and clarify the evaluation results of and provide data on horizontal city comparisons, which can be used to develop evaluation technology for sustainable development in cities and construct a standardized system. The results provide a standard framework for intelligent assessment and decision-making regarding cities’ sustainable development capabilities in China. Evaluating major international standardization institutions reveals that the practices of Chinese national standards should be fully absorbed and integrated to guide the evaluation of smart, resilient, and low-carbon cities. To this end, an indicator library of city sustainable development is proposed to provide standard evaluation technology methods. Finally, analyzing the response relationship of the indicator library to SDGs reveals the need for a standardized knowledge map of sustainable development assessment techniques and methods from the perspective of integrated management for sustainable development in cities.

Pelatihan Geotagging dan Layout Peta untuk Organisasi Perangkat Daerah Kabupaten Ogan Ilir

Geospatial data and technology are critical in a country's sustainable development process. Regional Apparatus Organizations (OPD) are essential in implementing regional government, which requires knowledge and understanding of geospatial data and technology to support better decision-making in a region. One way is through Geotagging training for ODP to increase knowledge, utilization, and competency in human resources in the geospatial field. The target of this training is the Ogan Ilir Regency OPD in South Sumatra Province. Training is held face-to-face using lecture and practice methods. Participants are given modules and receive direct guidance during the training process. The output of this training shows a significant increase in participants' understanding of geospatial data and the use of geotagging both theoretically and practically, which can be assessed from the presentation of the results of the tasks they have completed. This activity is a provision for ODP Kab. Ogan Ilir to be able to manage geospatial data and information.

Accelerated Development and Optimization of Adiponitrile Production via Kolbe Electrolysis of Biomass-Derived Precursors

Environmental and societal pressures are demanding a transition from fossil-based resources to renewable and sustainable feedstocks for the production of materials. In this context, biomass streams emerge as scalable candidates for creating sustainable chemicals. Electrocatalytic transformation of biomass can facilitate the production of chemicals under mild conditions and can be easily integrated with renewable energy sources. These transformations could lead to the production of sustainable monomers and polymers from biomass, significantly enhancing the sustainability of plastics production. Amongst a large number of plastics manufactured by the chemical industry, Nylon 6,6 is one of the most important fossil-derived polymers for the production of high-performance textiles and structural materials. Central to Nylon 6,6 production is adiponitrile (ADN), predominantly synthesized via energy-intensive thermochemical processes. An alternative route, electrochemical hydrodimerization of acrylonitrile (AN), although successful, still depends on fossil feedstocks. A promising sustainable source for ADN is renewable glutamic acid, derived from hydrolysis of waste proteins.1,2 This process involves transforming glutamic acid to 3-cyanopropanoic acid (CPA) and then to ADN through Kolbe electrolysis, a reaction with a historical background and multiple pathways. Our study utilizes an electrochemical reaction engineering approach to examine the Kolbe electrolysis of CPA to ADN and AN, focusing on a hierarchical research methodology. This approach allowed us to simultaneously accelerate the exploration of numerous reaction parameters while also conducting detailed studies under optimal conditions. This method has enabled us to gain deeper insights into the factors controlling reaction selectivity. We discovered that platinum electrodes favor ADN formation, with selectivity increasing at higher current densities. Optimal CPA concentrations, the presence of larger alkali cations, solvent composition, and controlled pH levels significantly influence ADN production, reducing side reactions such as the oxygen evolution reaction (OER). When using graphite electrodes, an increase in AN production was observed, with the solvent composition playing a crucial role in determining the rate of ADN formation. Our investigation has led to a deeper understanding of the electrochemical conversion of CPA to ADN, revealing key parameters that influence reaction selectivity and rate. The insights obtained from this study are not only pivotal for the specific case of ADN production but also have broader implications for a range of electrochemical decarboxylation reactions. The hierarchical research approach employed here demonstrates its potential for speeding the development of sustainable electrochemical processes. Our insights and methodology used for the electrosynthesis of ADN from biomass-derived feedstocks can be deployed to the deployed to the development of other biomass transformations advancing our ability to produce essential chemicals sustainably.

Understanding the Effects of Forced and Bubble-Induced Convection in Transport-Limited Organic Electrosynthesis

Organic electrosynthesis offers a sustainable path to decarbonize the chemical industry by integrating renewable energy in chemical manufacturing. However, achieving the selectivity and energy efficiency required for industrial applications is challenging due to the inherent mass transport limitations of most electro-organic reactions. Electrochemical reactions rely on transport of reactants to the electrode surface and become mass transport-limited when the reactant diffusion rate is lower than the reaction rate at the electrode. In organic electrosynthesis with several possible products, mass transport limitations can result in decreased selectivity towards the desired product as the various reaction pathways compete. Convection can mitigate mass transport limitations, but fundamental engineering guidelines for selecting and scaling up convection methods in electrochemical systems do not exist. As a result, the impact of convection on industrial-scale complex organic electrochemical processes remain poorly understood. Here we show that the Sherwood number (Sh)—the ratio of convective mass transport to diffusive mass transport—is a crucial metric to characterize mass transport, determine reactor performance, and enable effective scale-up. We investigate the interplay between mass transport and electrochemical reaction rates under convective flows in the context of the electrosynthesis of adiponitrile, one of the largest organic electrochemical processes in the industry. We use experiments and data-driven predictive models to demonstrate that forced liquid convection and bubble-induced convection produce nearly equivalent mass transport conditions when the corresponding Sherwood numbers are equal. This conclusion shows that the Sherwood number characterizes the mass transport condition independent of the underlying convection mechanism. Additionally, we show that the reactor performance scales with the Sherwood number for a given current density and reactant concentration. This scaling enables accurate prediction of performance irrespective of the convection method, and demonstrates that adiponitrile Faradaic efficiencies of >80% can be achieved for current densities of up to 200 mA/cm2 when Sh > 100. Our results provide guidelines for the design and selection of convection methods, from lab to industrial scale, and contribute to the development of more sustainable chemical manufacturing processes.

Promising non-model microbial cell factories obtained by genome reduction.

The development of sustainable processes is the most important basis to realize the shift from the fossil-fuel based industry to bio-based production. Non-model microbes represent a great resource due to their advantageous traits and unique repertoire of bioproducts. However, most of these microbes require modifications to improve their growth and production capacities as well as robustness in terms of genetic stability. For this, genome reduction is a valuable and powerful approach to meet industry requirements and to design highly efficient production strains. Here, we provide an overview of various genome reduction approaches in prokaryotic microorganisms, with a focus on non-model organisms, and highlight the example of a successful genome-reduced model organism chassis. Furthermore, we discuss the advances and challenges of promising non-model microbial chassis.

Greening the production of polymeric submicron particles by membrane-based manufacturing processes: A comparative analysis

The production of polymeric particles is the subject of extensive research in various fields and the interest in this area extends to the development of new sustainable production processes. The use of membrane technology has enabled the redesign of many traditional production processes with enormous impact in terms of product quality, reduction of energy consumption, high efficiency, productivity and reproducibility. In the present work, two alternative methodologies for the production of polycaprolactone (PCL) particles based on the use of membrane processes were investigated: i) membrane emulsification (ME) combined with solvent diffusion and ii) membrane nanoprecipitation (MN). ME/solvent diffusion is a widely applied technique for the production of microparticles, but its use for nanosized particles is still limited. On the other hand, MN is currently being investigated for its potentiality in the production of nanoparticles.In the present work, the performance of the two processes is compared in terms of: i) product quality (highly monodisperse particles in the nanometers range of size, ii) maximum productivity (expressed as mass of particles produced over time) under mild operating conditions (reduced mechanical stress), iii) environmental impact (assessed on the basis of the metrics established by the Green Aspiration Level (GAL)).

A novel logistic regression-embedded 0–1 mixed-integer probabilistic robust design model to obtain optimum sustainable factor settings

Quality by design (QbD) focuses on satisfying the needs of products or processes when aiming for variance reduction. On the other side, sustainability is associated with carrying on to conduct so over time. The research gap is also addressed in sustainability and QbD in this paper. Next, robust design (RD) is a suitable approach to QbD to reduce the process or product variation regarding quantitative and qualitative design factors. For a number of situations, a binomial random response variable is considered to decrease the variability of the production process. Thus, this paper is four-fold. First of all, a modified distance-based criterion is developed to generate the design matrix when dealing with quantitative and qualitative design factors. Second, a logistic regression technique is presented for modeling responses when the random response variable is binomial. Third, a new logistic regression-based 0–1 mixed-integer probabilistic RD model is proposed to find optimum sustainable design factors. Fourth, an Industry 4.0 associated case study is performed in order to design sustainable process development, and the comparison and verification studies are also presented to show the effectiveness of the proposed probabilistic model. Further, managerial insights are provided based on the sustainable development goals (SDGs).