Steel components used in automotive body and suspension structures are exposed to atmospheric conditions and therefore prone to corrosion over time. In addition to aesthetic degradation, corrosion negatively affects mechanical performance and service life. To prevent these effects, automotive manufacturers rely on coating and painting systems applied on the final assembled part. Consequently, manufacturing processes performed before painting, particularly welding, play a critical role in determining paint adhesion performance. This study investigates the influence of gas metal arc welding (GMAW) parameters on paint adhesion and coating integrity in automotive suspension components. The primary objective is to identify and optimize welding-related design parameters affecting paint adhesion using a Design for Six Sigma (DFSS) methodology. Different sheet materials, sheet thicknesses, and welding parameter combinations were systematically evaluated. The results indicate that lower sheet thickness is the dominant factor influencing paint adhesion, mainly due to increased heat transmission during welding. In contrast, variations in welding current, welding speed, and torch orientation exhibited negligible effects within the investigated parameter range. Signal-to-noise ratio analysis showed that increasing the lower sheet thickness from 1 mm to 5 mm improved paint adhesion performance by up to 40%, according to ISO 2409 classification for industrial automotive applications.

This paper presents a robust energy management strategy framework combining Design for Six Sigma (DFSS) and long short-term memory (LSTM). Various driving uncertainties affecting plug-in hybrid electric buses (PHEBs) are explicitly addressed. First, the segmented equivalent fuel consumption minimum strategy (ECMS) is developed as the foundational energy management framework. In the offline phase, a robust equivalent factor (EF) sequence for a single driving cycle is designed using the DFSS methodology to account for uncertainties in resistance coefficients and passenger loads. Then, the LSTM is trained with road segment speed clustering labels alongside the robust EF sequence, enabling the online generation of these robust parameters for new driving cycles. By referencing the actual historical speed data, the EF sequence for the entire driving cycle can be proactively designed to mitigate the impact of speed uncertainties. The simulation results show that the robust energy management strategy achieves lower fuel consumption expectations and standard deviation compared to the deterministic design. The results of HIL test substantiate the validity and effectiveness of the proposed robust design method.

The modified asphalt with high softening point was prepared by air oxidation polymerization with coal liquefied asphalt as raw material. The quality control model regarding the coking value and softening point of the product were established based on the DFSS (Design for Six Sigma) and RSM (response surface method). By means of elemental analysis, infrared, XPS, XRD, nuclear magnetic, MALDI-TOF and other characterization methods, the composition and structure characteristics of the modified asphalt were analyzed. Using the target product as raw material, general base asphalt carbon fiber was prepared by spinning, pre-oxidation and carbonization. The results show that the fitting effect of the quality control model about the coking value and softening point of the product is good, and the operating window range of the polymerization process parameters corresponding to the preparation of target product is wide. It can be found that the oxidation time and oxidation temperature has the most significant effect on the coking value and softening point of products, respectively, and all of them show a positive correlation. The dealkylation reaction and oxidative crosslinking reaction were carried out at the same time, and the bridging products of methylene bridging products, ether–oxygen bonds, carbonyl bonds, anhydride bonds and other oxygen-containing groups were generated. The properties of carbon fiber prepared with the target product are better: the tensile strength is 775 MPa, the elastic modulus is 68.6 GPa and the elongation at break is 1.13%.

Industry 4.0, also known as the Fourth Industrial Revolution, has completely changed the manufacturing landscape by utilizing technology 4.0 to increase productivity, efficiency, and flexibility.Setting priorities for technology is crucial to achieving the best possible implementation as manufacturing companies transition to Industry 4.0.This abstract provides a framework that combines the Design for Six Sigma (DFSS) approach with multi-criteria decision-making (MCDM) methods to assess the readiness of manufacturing firms for Industry 4.0 adoption.At the core of the DFSS approach, we specifically utilized MCDA in the analysis phase, focusing on the key considerations and challenges.A comprehensive assessment of technologies, including artificial intelligence (AI), the Internet of Things (IoT), cyber-physical systems (CPS), augmented reality (AR), and big data, is part of the prioritizing process.Investment expenses, system integration complexity, security, and return on investment are key evaluation criteria.We also used Factory IO software in the last phase of the DFSS approach to verify, test, validate, and optimize process designs prior to real implementation.Experts can prioritize technologies that support their strategic objectives by using this approach.This study contributes a structured pathway for manufacturing industries to navigate the complexities of digital transformation with an emphasis on expert precision and quality improvement.

Purpose Identifying and prioritizing the Design for Six Sigma (DFSS) critical success factors (CSFs), based on the supplier integration and process integration factors in the supply chain of the home appliance industry. Design/methodology/approach The literature has been reviewed and the viewpoints of 20 experts in the relevant industry have been studied. The Pareto principle has also been used to select the most important factors obtained. Finally, to prioritize the most important selected factors of DFSS, a model has been developed with a two-stage Fuzzy House of Quality (FHoQ). To perform this research and consider that Polar Heating and Cooling Manufacturing Company (PHCMC) is one of the pioneers of the home appliance industry in recent decades in Iran, the supply chain of its chimneyless gas heater product has been considered as the case study. Findings Findings indicated that the priorities of the CSFs of DFSS based on the definite weights obtained from the results of the research model are linking Six Sigma to suppliers, project management, linking Six Sigma to business strategy, linking to organizational learning, considering customer needs and management commitment, respectively. Also, the priorities of supplier integration factors based on the definite weights obtained from the model are suppliers’ partnership, information sharing, top management commitment and support, supplier strategic integration, cost, and supplier evaluation and selection, respectively. Practical implications According to the findings, it is recommended that the design, research and development unit focus more on the processes and opinions of suppliers and with the special use of data categorization software such as MATLAB, it is also possible to improve the processes and optimize them in further integration of the supply chain. It is also possible to improve the suppliers’ integration in the supply chain with the help of correction analysis and improvement tools in the field of quality management. Originality/value Supplier integration, process integration and DFSS are three strategic areas in supply chain management that have been addressed in this research, simultaneously. The use of two-stage FHoQ, in obtaining the priority design for the CSFs of DFSS, is one of the significant innovations of this study, which can be used for greater supplier integration and also to improve supply chain integration.

PurposeThe purpose of this study is to develop a systematic approach by demonstrating the Design for Six Sigma (DFSS) approach for reliability improvement of moulded case circuit breaker (MCCB) (current rating 250A).Design/methodology/approachIn this study, the Define, Measure, Analyze, Design and Verify (DMADV) methodology of DFSS has been used to improve the reliability of MCCB. Mechanical endurance test (MET), project risk management, customer-based product development (PD), and other tools and techniques are used appropriately in DMADV methodology for improving the reliability of MCCB.FindingsIt has been observed that the reliability of MCCB has been improved from 61.76% to 98.17% for 20,000 operating cycles by implementing suggested improvement measures and the Weibull distribution is the most suitable distribution for reliability analysis of collected data.Research limitations/implicationsThis study considered only the aspects of DMADV methodology of the DFSS approach and does not cover other PD approaches such as lean and green PD.Practical implicationsThis study clearly shows an enhancement in the reliability of MCCB which further leads to an increase in the warranty period. This will attract more customers and enhance business.Social implicationsThe improvement in the reliability of MCCB would significantly reduce fatal accidents ensuring workplace safety in the industry.Originality/valueThe originality of this study is the reliability assessment using degradation analysis in the design phase of the DMADV process to predict failure during design verification.

Flux-switching wound field machines (FSWFMs) offer high torque density and independence from rare-earth materials, making them promising candidates for sustainable electric vehicles and industrial applications. However, their adoption is limited by challenges such as high torque ripple, efficiency variations, and sensitivity to manufacturing tolerances. This study presents a Design for Six Sigma (DFSS) optimization framework that integrates sensitivity analysis, response surface modeling (RSM), and multi-objective genetic algorithms to address these challenges. The optimized solution reduces torque ripple by 7.69%, improves torque output, and enhances energy efficiency. By incorporating Six Sigma principles, the framework ensures robust performance under manufacturing variations, bridging the gap between theoretical optimization and practical implementation. This scalable and efficient methodology establishes FSWFMs as viable solutions for industrial applications, revolutionizing electric machine design.

Plug-in fuel cell electric buses (PFCEBs) have the potential to effectively reduce energy usage through efficient energy management. However, when PFCEBs operate on non-fixed bus routes, noise factors such as driving cycle, stochastic vehicle mass, and driving distance make it challenging to achieve optimal fuel economy. To tackle this issue, this study introduces an adaptive energy management control method for PFCEBs operating on non-fixed bus routes, considering the aforementioned factors. Firstly, an adaptive energy management control method based on the algorithm of Pontryagin’s Minimum Principle (PMP) is proposed to be integrated into the energy management system, allowing for real-world adaptive control. Secondly, a Design for Six Sigma (DFSS) methodology is proposed to address the noise disturbance problem caused by the driving cycle, stochastic vehicle mass, and driving distance. The main objective of DFSS is to find the “flat” zone of the design space (constituted by co-state and normalized distance), whilst minimizing the mean hydrogen consumption and its standard deviation. Validation results from Monte Carlo Simulation (MCS) demonstrate the effectiveness and applicability of the DFSS methodology in the energy management design for PFCEBs operating on non-fixed bus routes. Furthermore, simulation results indicate that the proposed robust co-state design method can achieve fuel economy comparable to that of an off-line PMP control strategy. In comparison to the rule-based strategy, the fuel economy improves by an average of 18.01%, 20.06%, and 18.91% for bus route 1, 2, and 3, respectively.

Design for Six Sigma (DFSS) is a statistical methodology for improving the quality of processes and their organizational areas worldwide used since the 80’s. However, most of the existing laboratories for obtaining experimental results, which validate theoretical proposals that are being studied in the microgrids research field, have been designed without following any roadmap. The purpose of this study was to develop a microgrid station for research and teaching at the Power Electronic Laboratory of Escola Politècnica Superior d Enginyeria de Vilanova i la Geltrú (EPSEVG) based on a DFSS tool called IDDOV, which stands for Identify, Define, Develop, Optimize, and Verify. An IDDOV roadmap to conduct a laboratory design development is provided and applied to design a laboratory at EPSEVG in this study. The results show that a well-structured roadmap, such as IDDOV, promotes a culture of continuous improvement for the microgrid research bed, encouraging feedback from users and stakeholders to identify opportunities for improvement. The conclusion of this paper highlights the benefits of using the DFSS conceptual methodology to develop a microgrid station for research and teaching, such as adaptation to educational needs; enhancement of the learning experience; refutation of experimental errors; cost-effective, flexible, and modular design; collaborative learning environment; data-driven teaching; and continuous improvement. As electrical grids are dynamic systems in constant evolution, a new IDDOV roadmap should be carried out in future studies, to enhance the test bed recommended here.

The modern economic landscape, now more competitive than ever, compels companies to create increasingly innovative, cutting-edge, and cost-effective products. In this regard, the design and development phases play a crucial role, as they closely determine the final satisfaction of the customers. It follows from this the need for a structured approach to product development, which allows companies to identify product key characteristics, also useful when there is the need for carrying out the redesign of an existing product. This work provides the application of the Design For Six Sigma (DFSS) methodology to a real redesign case study, based on the improvement in a specific mountain bike model (baseline product). The final target is identifying the main criticalities and intervention areas for the bicycle, to provide valuable suggestions to designers and developers for creating a new product alternative characterised by an extended horizon to various markets. DFSS is applied to identify and optimise Critical-To-Quality (CTQ) features, aiming at making the project as responsive as possible to customers’ needs. More specifically, two main tasks are addressed. The first one is the application of the identify phase of the IDOV approach (Identify, Design, Optimise, Validate) to identify the most pertinent Voice of the Customers (VOCs) to be implemented in the product. The second main task is the analysis of the integrated product development process carried out through the Six Sigma (SS) methodology, to transform the VOCs into CTQs via the Quality Function Deployment 1 (QFD1) and to prioritise the CTQ to achieve design excellence. The identified improvement strategies are presented and critically discussed in relation to their potential to reduce the environmental impact of the overall Life Cycle (LC) of the product.

PT XZY is a company in the industrial sector that produces instant noodles. In the production process, PT XZY faces several problems that cause product defects, especially in the packaging of Bumbu Oil Mie Goreng (BOMG). This packaging has several deficiencies such as quality defects (squashed packaging, folded edges, contents not up to standard) and unstable productivity. Therefore, this study aims to identify the factors that affect product defects and conduct development to improve quality and productivity. This research uses the Design for Six Sigma (DFSS) method with the stages of Define, Measure, Analyze, Design (DMAD). Based on the results of research using the design from six sigma method, it states that the highest sigma value of defects occurs with a total sigma value of 2,910 and also produces the highest value of defects in the noodle packaging squash factor of 38% resulting from the Pareto diagram.

Design for Six Sigma (DFSS) is a critical component of the Six Sigma methodology, focusing on product, process, and service design. DFSS is proactive, focusing on design rather than existing processes. Its wide application in various sectors, from manufacturing to service industries, has proven its effectiveness. Despite this, its adoption in education remains limited. This research explores the application of DFSS in education, particularly in redesigning a course through gamification to enhance student engagement. This study addresses this gap by illustrating how DFSS principles can enhance education, mainly through gamification. Gamification, incorporating game elements into learning, holds promise for engaging students and improving learning outcomes. Using the DMADV framework, the study defines project objectives, gathers the voice of the customer using the Kano model, analyzes survey data, designs gamification elements, and verifies their effectiveness through student feedback. Results indicate several attractive elements identified through the Kano model, such as smartphone integration and clear rules. Implementation challenges, particularly in a Jeopardy-style review session, are identified and addressed using DFSS tools such as failure mode and effects analysis. Subsequent surveys capture student feedback and suggest improvements, highlighting the iterative nature of DFSS. The study underscores the potential of DFSS in educational redesign, particularly through gamification, to enhance student engagement and learning outcomes. While focused on a specific course, the methodology's generalizability and applicability to diverse educational contexts warrant further exploration for broader implementation.

Although coal mining business provide a large economic contribution, coal mining operational can have negative impacts if that business don’t implement good mining practice. Therefore, companies need to optimize technology to minimize negative impacts and increase productivity. The problems that have occurred at PT. Kideco Jaya Agung is an information system that is currently implemented is not yet relevant according to the stakeholders expectation. Data error, bugs, and mistake found, so there will be potential for dualism point of view which can impact to fault in decision making. So strategic planning in information system is needed with the aim that the company designs a concept which is effective and has the best quality in accordance with stakeholder needs to support the company's business. The application of Design For Six Sigma (DFSS) is to analyze planning based on stakeholder needs, then the used tools is Software Quality Function Development (SQFD). SQFD tool quantifies user needs and then prioritizes the digitalization project portfolio by mapping all user needs involved in the business process. Design For Six Sigma analysis produces output analysis of stakeholder needs. Based on stakeholder needs, the business processes required to be digitized include Coordination Meetings, Data Analysis, Daily/Weekly/Monthly Reports, Contractor/Subcont Management, and Decision Making which then become a reference in designing data flow diagrams as conceptual design.

The robust design of a new product is exemplified in this paper as an exercise that every engineering student could do for a better understanding of the DFSS (”Design For Six Sigma”) process. The design of a new paper binder is presented through several steps that make the process easy to follow and to understand by the student. Both classical mathematical pursuit and modern technology are presented as viable ways of solving the problem.

Introducción La pandemia de COVID-19 implicó grandes impactos en lo sanitario, económico y social. Más aún, mantener la distribución de productos esenciales para responder a la pandemia, expuso a trabajadores de distintas empresas y servicios públicos al contagio por enfermedad COVID-19, especialmente al inicio de la pandemia en donde las vías de transmisión del virus aún no estaban definidas y, por lo tanto, las medidas laborales que se debían implementar para proteger a los trabajadores. En Chile, las empresas y servicios públicos también se vieron obligadas a adaptarse a las diversas directrices que la autoridad sanitaria fue estableciendo para evitar el, contagio de los trabajadores esenciales y, posteriormente, para las fases de apertura de acuerdo a la respuesta a la emergencia sanitaria. La responsabilidad para la trazabilidad de dichos contagios recayó en las autoridades sanitarias regionales del país. Objetivos Describir el diseño y aplicación de un proceso de detección de contactos estrechos y casos positivos para enfermedad por COVID-19 con trazabilidad laboral en la Región de Los Ríos, Chile 2021-2022 Método Se llevó a cabo un estudio descriptivo, basado en la metodología Design For Six Sigma (DFSS), específicamente la DMADV (definir, medir, analizar, diseñar y verificar). La metodología se utilizada para la creación o rediseño de un nuevo producto o proceso, por lo cual, y considerando el vacío de un procedimiento estándar para enfrentar la emergencia sanitaria, se utilizó dicho método para la creación de un proceso de detección de casos COVID-19 con origen laboral. La creación del proceso involucró la coordinación entre los organismos administradores de la ley presentes en la región y la unidad de investigacion laboral de la sección de epidemiología de la Secretaría Regional Ministerial de Salud de la Región de los Ríos. Para el diagrama de flujo del proceso se utilizó el programa Bizagi. La recolección de la información se llevó a cabo desde el 01 de enero de 2021 hasta el 31 de diciembre de 2022. Una vez aplicado el proceso de detección de casos, los resultados fueron analizados mediante distribución de frecuencias y medidas de tendencia central. Resultados principales Se detectaron un total de 10.520 contactos estrechos de origen laboral en la región de Los Ríos, cuya media de edad fue de 37,7 años, concentrándose en el grupo etario de 25 a 44 años con el 60,2% (6.336) del total de casos. Con respecto a su distribución por sexo, la mayoría de los casos correspondieron a mujeres con un total del 53% (5.580) de los casos. La de Comisión de Medicina Preventiva e Invalidez (COMPIN) de la Región de Los ríos debió aplicar al 3,8% (407) de los casos detectados, el artículo 77 bis de la ley 16.744. Estos casos correspondieron al 39,2 % del total de los 77 bis administrados por la COMPIN durante el período del estudio. Conclusiones El diseño e implementación de un proceso de detección de casos de COVID-19 con origen laboral, permitió no solo una mejor trazabilidad sino también una derivación efectiva y oportuna producto de la aplicación del artículo 77 bis, para que la Superintendencia de Seguridad Social pudiese resolver las prestaciones a cargo a un régimen previsional diferente al propuesto inicialmente.

In today's fast-paced and complex market environment, companies face the challenge of continuously developing new and high-quality products that meet customers' evolving demands and technological advancements while also considering economic, environmental, and social factors. More than simply understanding customers is required; companies must prioritize addressing their needs and exceeding their expectations. However, creating new and innovative products can only be challenging with a systematic and comprehensive approach. This paper proposes an advanced process for new product development by integrating the Theory of Inventive Problem Solving (TRIZ) with the existing Design for Six Sigma (DFSS) methodology. A case study of the design of teabags is presented to demonstrate the effectiveness of this framework. By using this integrated approach, companies can better understand their customers' needs and create innovative, high-quality products that exceed expectations.

Plug-in fuel cell electric bus (PFCEB) is taken as one of the most promising technical ways for the sustainable and healthy development of the vehicles. However, the energy saving potential has not been exhaustively tapped, because of the limited integrated design (component matching design together with the energy management) level. This paper proposes a robustly integrated design method to address the issues. Firstly, a Taguchi robust design (TRD) method considering the noise of components, stochastic vehicle mass and historical driving cycles is proposed to find the robust design parameters that are suitable for different component matching and can resist the noise disturbance. Then, a component matching design zone reduced work is finished through analyzing the mechanism of action between components and the evaluation index, based on the TRD theory and the Sensitivity analysis method (SAM). Finally, a robust component matching design method is investigated by considering the noises, based on the Design for Six Sigma (DFSS) theory. The simulation results demonstrate that the TRD and DFSS methods are reasonable and applicable in the integrated design of PFCEB, where the robust component matching can be found; the energy economy of the proposed adaptive Pontryagin’s Minimum Principle (A-PMP) based energy management strategy is better than the rule-based control strategy.

Purpose This research proposes how Design for Six Sigma (DFSS) provides a complementary approach for business process management (BPM) lifecycle implementation in order to address gaps identified in the current literature. Design/methodology/approach The mandatory elements of a method (MEM) framework is used to illustrate DFSS's maturity as a process redesign method. The use of DFSS in a BPM context is described through several action research case examples. Findings This research specifies the procedure model (order of development activities), techniques, results, roles and information/meta model (conceptual data model of results) associated with using DFSS to address BPM-related challenges. The action research case examples provided discuss the details of implementing BPM using DFSS to design, implement and test redesigned processes to ensure they fulfill the needs of process participants. Research limitations/implications While the case examples discussed were performed in only a few settings, which limits the generalizability of their results, they provide evidence regarding the wide range of domains in which the proposed DFSS-BPM approach can be applied and how the tools are used in different contexts. Practical implications This research offers a road map for addressing the challenges practitioners often face with BPM lifecycle implementation. Originality/value This research provides the first attempt to integrate DFSS as a complementary method for BPM lifecycle implementation.

The transition to digital manufacturing has become more important as the quantity and quality of the use of computer systems in manufacturing companies has increased. It has become necessary to model, simulate and analyse all machines, tools, and raw materials to optimise the manufacturing process. It is even better to determine the best possible solution at the stage of defining the manufacturing process by using technologies that analyse data from simulations to calculate an optimal design before it is even built. In this paper, Design for Six Sigma (DFSS) principles are applied to analyse different scenarios using digital twin models for simulation to determine the best configuration for the manufacturing system. The simulation results were combined with multi-criteria decision-making (MCDM) methods to define a model with the best possible overall equipment effectiveness (OEE). The OEE parameter reliability was identified as the most influential factor in the final determination of the most effective and economical manufacturing process configuration.

The current paper aims to present a cooling concept for future centralized platforms of ECUs (Electronic Control Units) from the automotive industry that involves grouping multiple electronic devices into a single system and cooling them with forced convection dielectric coolant. The enhancement consists of replacing the inside air of the module with a dielectric coolant that has a higher thermal conductivity than air and employing an additional prototype system that aids in forced liquid cooling. To meet automotive requirements, the experiments were exposed to an ambient temperature of 85 °C. Temperature measurements on these solutions’ hot spots were compared to those on a thermal paste-only reference electronic module. This study used DFSS (Design for Six Sigma) techniques to determine the ideal pump flow rate, fan air flow rate, and liquid volume in the housing, leading to an optimization in heat dissipation. Finding a trustworthy transfer function that could forecast the impact of the crucial design parameters that had been found was the main goal. The electronics cooled by forced convection coolant improved heat dissipation by up to 60% when compared to the reference module. This demonstrates that the DoE (Design of Experiments) method, which is based on a limited number of measurements, can estimate the behavior of the ECU without the need for a more involved theoretical framework.