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Currently, the development of renewable energy products (RES) encourages the search for innovative solutions that take into account key criteria from the point of view of their sustainable development. Despite efforts in this area, there is a lack of approaches and tools to support this process. Therefore, the aim of the research was to develop a decision-making model supporting eco-innovation in products based on the key criteria of sustainable development: quality (customer satisfaction with use), environmental impact in the life cycle (LCA), and the cost of investment incurred in the product development. The functioning of the model was based on the following factors: (i) obtaining the voice of customers (VoC) and processing it into product criteria as part of the development of alternative production solutions (prototypes), (ii) prospective quality assessment and subsequent life cycle assessment of prototypes, (iii) cost analysis taking into account both quality and environmental criteria, (iv) interpretation of results and search for eco-innovative product solutions. Development decision-making is additionally supported by techniques implemented in the model, e.g., the CRITIC method, the LCA method with Ecoinvent database in OpenLCA, the CEA method, and the morphology method. The model was illustrated and tested for photovoltaic (PV) panels, after which a global sensitivity analysis was performed in Statistica. The test results showed that the main factor that influenced the PV development decisions was the investment cost, followed by quality (customer satisfaction) and then environmental impact in LCA. [ABSTRACT FROM AUTHOR]

The sustainability of products remains a challenge, mainly due to the lack of consistent approaches for simultaneously taking into account the key criteria of the concept in the process. This research aims to develop an eco-innovative QLCA method to create new product solutions that integrate quality (customer satisfaction) and environmental impact assessment throughout the product life cycle. The QLCA method includes: (i) product prototyping according to quality and environmental criteria; (ii) prospective assessment of the quality of prototypes, taking into account customer requirements; (iii) prospective life cycle assessment of product prototypes using a cradle-to-grave approach in accordance with ISO 14040; and (iv) setting the direction of product development while taking into account the fulfilment of customer expectations and the need to care for the environment throughout the product life cycle. Owing to the lack of previous research in this area, as well as the popularity of photovoltaic (PV) panels in reducing greenhouse gases, an illustration was obtained and test of the method was carried out on the example of silicon photovoltaic panel modules (Crystalline Si PV Module). In accordance with the adopted assumptions, the results of the QLCA method test showed that the modelled PV prototypes will, in most cases, be satisfactory for customers, but they still require improvement actions to reduce carbon dioxide (CO2) emissions throughout their life cycle. These activities should be consistent so as to achieve quality that satisfies customers. The QLCA method can be used by designers, managers, and decision-makers at the early stages of design, but also during the product maturity phase for its sustainable development. [ABSTRACT FROM AUTHOR]

The development of materials and the products made from them should respond to new challenges posed by market changes and also by climate change. Therefore, the objective of this investigation was to develop a method that supports the sustainable development of materials and the products made from them based on an aggregated indicator of quality and environmental load in the life cycle (QLCA). The testing and illustration of the QLCA method included a passenger car tyre and nine prototypes. These prototypes were described using eight quality criteria: season, class, size of the load index, speed index, rolling, adhesion, and external noise. Then, customer expectations regarding the importance of the criteria and satisfaction with the indicators in the current and modified states were obtained. Based on the customer assessment, the quality indicators of the prototypes were assessed. This assessment was supported by the weighted sum model (WSM) and the entropy method. Then, life cycle assessment for the reference tyre was performed using the Ecoinvent database in the OpenLCA program. LCA indicators were modelled for other prototypes, taking into account quality changes. As a result of the verification of the method, an aggregated QLCA indicator was estimated, based on which it was possible to select the most favourable (qualitatively and environmentally) prototype out of nine. This was the P4 prototype (QLCA = 0.57). The next position in the ranking was taken by P7 (QLCA = 0.43). The QLCA method can be used to determine the direction of development of materials and products in terms of their sustainable development. [ABSTRACT FROM AUTHOR]

While there are software tools available for helping to conduct life cycle assessment (LCA), such as OpenLCA, these tools lack integration with process design, simulation, and optimization software. As LCA has a critical role in sustainable product design, this paper presents a platform called EMSO_OLCA, which integrates the LCA provided by OpenLCA into the Environment for Modeling, Simulation, and Optimization (EMSO). EMSO_OLCA incorporates a database of environmental impact assessment methodologies from OpenLCA and aligns with the principles of LCA outlined in ISO 14040 and ISO 14044. Validation tests were conducted to compare the results obtained by the LCA of sugarcane ethanol using OpenLCA and EMSO_OLCA, revealing a high level of agreement. The average relative error was 0.045%, indicating a negligible discrepancy between the tools. Moreover, it took only 0.3 s for the calculation, which is desirable for use with process system engineering tools. A second case study was applied to combined steam and electricity production from the combustion of sugarcane bagasse and straw in a combined heat and power system. The results show the integration of LCA with simulation and sensitivity analysis tools, thus supporting sustainable decision-making processes. EMSO_OLCA bridges the gap between LCA and process engineering, enabling a holistic approach to the sustainability, design, and implementation of environmentally friendly solutions. [ABSTRACT FROM AUTHOR]

This paper aims to develop an integrated Quality–Cost–Environmental (QCE) indicator for the selection of photovoltaic panels (PVps) offered to customers, considering the following criteria: (i) quality satisfaction; (ii) cost-effectiveness; and (iii) environmental impact throughout the life cycle. The proposed QCE indicator was developed within a framework that incorporated an FAHP (Fuzzy Analytic Hierarchy Process), cost-effectiveness analysis (CEA), and life cycle assessment (LCA). The model test confirmed its effectiveness in choosing a PVp which combines environmental friendliness throughout its entire life cycle with satisfactory quality and a reasonable purchase price for customers. The proposed model can be utilized by individuals, businesses, and public entities for the selection of high-quality, cost-efficient, and environmentally friendly PVps—thereby promoting sustainable development. [ABSTRACT FROM AUTHOR]

Sustainable product development requires combining aspects, including quality and environmental. This is a difficult task to accomplish. Therefore, procedures are being sought to combine these aspects in the process of product improvement. Therefore, the objective of the investigation was to develop a procedure that supports the integration of quality-level indicators and life-cycle assessment (LCA) to determine the direction of product improvement. The procedure involves determining the quality indicators based on the expectations of the customer, which are subsequently processed using the formalised scoring method (PS). A life-cycle assessment index is determined for the main environmental impact criterion. According to the proposed mathematical model, these indicators are aggregated, and this process takes into account their importance in terms of product usefulness and environmental friendliness. Interpretations of the results and the direction of product improvement are from the results obtained from the modified IPA model (importance–performance analysis). The procedure is used in the verification of product prototypes, wherein the proposed approach, and its test, was carried out for a self-cooling beverage can (and its alternatives) with a "chill-on-demand" system, which is a technology supporting rapid cooling on demand. The life-cycle assessment was carried out to assess the carbon footprint, which is crucial for activities to reduce greenhouse gases. The direction of improvement of this product was shown to concern the selection of transport means, the reduction of energy use in the production phase, or the change of the method of opening the can. What is original is the proposal of a procedure for integrating the quality indicator and the life-cycle assessment indicator, taking into account the key environmental burden. The procedure can be used in manufacturing companies when designing and improving products in terms of their sustainable development. [ABSTRACT FROM AUTHOR]

Blue denim, a billion-dollar industry, is currently dyed with indigo in an unsustainable process requiring harsh reducing and alkaline chemicals. Forming indigo directly in the yarn through indican (indoxyl-β-glucoside) is a promising alternative route with mild conditions. Indican eliminates the requirement for reducing agent while still ending as indigo, the only known molecule yielding the unique hue of blue denim. However, a bulk source of indican is missing. Here, we employ enzyme and process engineering guided by techno-economic analyses to develop an economically viable drop-in indican synthesis technology. Rational engineering of PtUGT1, a glycosyltransferase from the indigo plant, alleviated the severe substrate inactivation observed with the wildtype enzyme at the titers needed for bulk production. We further describe a mild, light-driven dyeing process. Finally, we conduct techno-economic, social sustainability, and comparative life-cycle assessments. These indicate that the presented technologies have the potential to significantly reduce environmental impacts from blue denim dyeing with only a modest cost increase. Conventional blue denim dyeing has both environmental and health-related consequences. Here, Bidart et al. use enzyme engineering to develop a viable method for the bulk production of indican and demonstrate dying processes which could significantly reduce the negative consequences of this billion-dollar industry. [ABSTRACT FROM AUTHOR]

The advancement of quality and environmentally sustainable materials and products made from them has improved significantly over the last few years. However, a research gap is the lack of a developed model that allows for the simultaneous analysis of quality and environmental criteria in the life-cycle assessment (LCA) for the selection of materials in newly designed products. Therefore, the objective of the research was to develop a model that supports the prediction of the environmental impact and expected quality of materials and products made from them according to the design solution scenarios considering their LCA. The model implements the GRA method and environmental impact analysis according to the LCA based on ISO 14040. The model test was carried out for light passenger vehicles of BEV with a lithium-ion battery (LiFePO4) and for ICEV. The results indicated a relatively comparable level of quality, but in the case of the environmental impact throughout the life-cycle, the predominant amount of CO2 emissions in the use phase for combustion vehicles. The originality of the developed model to create scenarios of design solutions is created according to which the optimal direction of their development in terms of quality and environment throughout LCA can be predicted. [ABSTRACT FROM AUTHOR]

One of the global ecological problems is the excessive carbon dioxide emissions generated by vehicles in the transport sector, including passenger transport. Therefore, the objective of this investigation was to develop a model that supports the prediction of vehicle variants that will be satisfactory to the customer in terms of: (i) quality level and (ii) environmental impact throughout the life cycle. This model was developed with the following techniques: TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution), LCA (Life Cycle Assessment), SMARTER (Specific, Measurable, Achievable, Relevant, and Time-bound), Pareto–Lorenz, and the Multi-Criteria Decision Method rule (7 ± 2). A model test was carried out for production variants of the electric vehicle BEV (battery electric vehicle) for which the quality level and life cycle assessment were estimated. Vehicle quality levels ranged from 0.15 to 0.69, with a weight of 0.75. However, vehicle life cycle scores were estimated in the range of 0.25 to 0.57, with a weight of 0.25. Ultimately, the level of the vehicles' LCA ranged from 0.18 to 0.62. As a result, it was shown that on the basis of various modifications of the quality level of vehicle variants and the corresponding environmental impacts throughout their life cycle, it is possible to predict the vehicle variant that is most satisfactory for the customer and, at the same time, environmentally friendly. The originality of the model relies on supporting the making of sustainable design decisions and the planning of vehicle improvement actions according to customer expectations. Therefore, the model can be used to analyse different types of vehicles by producers and dealers of these products. [ABSTRACT FROM AUTHOR]

The early phases of product development effect fundamental changes in products throughout their life cycle. Therefore, the objective of the investigation was to develop a simplified model that supports the process of product design simultaneously in terms of qualitative and environmental factors. The model is dedicated to the design phase in the life cycle assessment of the product (LCA). The originality of the model consists in: (i) analysis of customers' satisfaction from qualitative alternatives of products; (ii) assessments of the environmental impact of these alternatives; (iii) definition of the importance of qualitative and environmental attributes of products; and (iv) prediction of favourable changes in products according to qualitative–environmental levels. The model was tested for photovoltaic panels (PVs). The model is mainly dedicated to small and medium-sized enterprises (SMEs) for support in making decisions in the design phases of products in their life cycles. [ABSTRACT FROM AUTHOR]

Sustainability is at the heart of continuous product improvement, where social, environmental, and economic considerations are key. This is a difficult task, especially in the area of the following economic and environmental changes, as well as changes in customer expectations. Additionally, it has become crucial to make product decisions that will be based on their entire life cycle (LCA). Although these aspects of sustainability and LCA are popular, bringing them together in one analysis remains challenging. Therefore, the article's objective was to develop a simplified model that supports decisionmaking, taking into account the criteria of sustainable development and life cycle assessment (LCA). The originality is the proposed model, which operates based on a qualitative indicator (product quality level), an environmental indicator (the product's impact on the environment throughout its life cycle) and a price indicator (purchase price of the product). These indicators are created using the TOPSIS method and the modified ACJ-E method. As a result, a product ranking is created. A novelty is the combination of Life Cycle Assessment (LCA) criteria with quality criteria and the actual purchase price of the product. The model test was carried out on the example of CATERPILLAR mini excavators. However, the model can be dedicated to any company that wants to make decisions in accordance with the idea of sustainable development. [ABSTRACT FROM AUTHOR]

This paper introduces an innovative model designed to predict the optimal product prototype within the framework of sustainable development. The model takes into account both quality and environmental impact throughout the entire life cycle of the product, with a specific focus on light electric vehicles. By incorporating customer expectations using the Weighted Sum Model, the model assesses vehicle quality based on the importance of various criteria. Employing life cycle evaluations guided by the Pareto-Lorenz rule, environmental impact for vehicle prototypes is modeled. The resulting Quality-Environmental Indicator of LCA (QLCA) facilitates a qualitative environmental analysis, aiding in the selection of prototypes that align with customer expectations. The model proves effective in guiding decisions related to product development, providing a comprehensive approach to evaluating product value. Notable contributions to the scientific community include the introduction of the QLCA model, which integrates quality and environmental assessments, and underscores the significance of open innovation, sustainable development, and sensitivity analysis for organizational adaptation. Future research directions involve adapting the model to larger customer samples, exploring production costs, and assessing its applicability across diverse industries and contexts to enhance its universality and practical implications. [ABSTRACT FROM AUTHOR]

Environmental concern requires manufacturers to extend the domain of their control and responsibility across the product's life cycle. Much of the research has concentrated on assessment of environmental performance through the application of the Life Cycle Assessment (LCA) framework that provides a technical methodology to help identification of environmental impacts of product systems. However, the current LCA framework does not incorporate dynamic and diverse characteristics of manufacturing processes. As a result, the LCA's referential data will largely deviate from the real ones to an extent that the purpose of LCA is not meaningful. In other words, the current and fixed referential data-based method is not suitable to specify the impact categories related to manufacturing processes. From the perspective of decision making related with environmental impact during manufacturing, the current LCA method carried out in the off-line is hard to apply. As a result, performance index, such as greenability, a major performance index for environment conscious manufacturing cannot be implemented in the real practice. This paper presents the development of a framework (called process-oriented LCA) to realize environmental conscious manufacturing incorporating both greenability and productivity. To show the applicability and validity of this framework, experiments and analysis have been conducted and a prototype system has been implemented for a turning machining process. [ABSTRACT FROM AUTHOR]