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This article synthesises the return of experience of performing a product variety analysis for a (supplier in the automotive sector) that haven't had yet a product variety management strategy. This paper is part of a multi-year research project on the design of reconfigurable production systems. The contribution is (i) to present at a glance the developed strategy of product similarity assessment and (ii) to underline the industrial benefits of this similarity assessment obtained as a result of the industrial case studies. First, the article reminds, in the context of product variety, a developed methodology to assess product similarities by four indices. These consider the functions, product structures and the way to assemble them. Second, the focus is put on the benefits of their application through three industrial use cases: during the design of a new product identifying its impact on the manufacturing system, identifying the fittest production line for a new product to assemble and generating a new adapted production line by gathering products belonging to the same product family. All benefits are illustrated through the results of the industrial case studies. These are anonymised due to confidentiality issues. [ABSTRACT FROM AUTHOR]

Simultaneous optimization of a family of related products can yield significant benefits compared to individual product optimization. Standardization of parts across different products and streamlining assembly and manufacturing processes can lead to reduced overall costs for the product family. In this study, we introduce a methodology for optimizing the design of a product family while considering detailed CAD models of individual products. The motivation arises from the challenge of achieving optimal product standardization without compromising individual product performance. Existing methods often impose predefined levels of commonality and seldom account for detailed CAD models and computationally expensive metrics of interest. To address this gap, we propose a novel approach that utilizes surrogate models to mitigate computational complexity and optimize the product family configuration based on total production cost, ensuring economically viable configurations while meeting performance requirements. The objective function incorporates the total production cost of the product family, including manufacturing and assembly process costs and volume discounts. Assembly process complexity and associated costs are quantified using Design for Assembly rules, while individual product performance, evaluated through finite element models, serves as a constraint. The results of the single-objective optimization, applied to a case study involving a product family comprising multiple gearboxes, demonstrate that by considering the product family, a better design in terms of the total production cost can be found compared to optimizing each product individually. Results indicate that the suggested method can efficiently identify optimal product family configurations, balancing standardization benefits with individual product performance. Overall, this study contributes to advancing methodologies for product family optimization and underscores the importance of considering detailed product designs in the optimization process. [ABSTRACT FROM AUTHOR]

This paper proposes a method for simultaneous evaluation of the assembly process complexity together with the performance of the future product. It allows for product design optimization, considering different aspects of the future design at the early stage of the development process. The proposed method, embodied in a fully automated framework, substitutes the traditional sequential development process with a more efficient and rapid combined procedure, which addresses multiple design aspects simultaneously. Design for assembly (DFA) rules, used as quantitative metrics of the ease-of-assembly of the whole product and individual assembly operations, are automatically evaluated together with performance metrics, estimated based on finite element (FE) simulations. The direct solution to this optimization problem might be inefficient or impossible since it requires the recurrent evaluation of computationally expensive discrete and continuous functions with unknown behavior that represent the optimization objectives and constraints. For that reason, the proposed framework employs regression models based on the Gaussian process and artificial neural networks, thus achieving the optimal design of a product as a result of metamodel-based design optimization (MBDO). The suggested approach is demonstrated in the optimization of a gearbox assembly, considering its mechanical performance and assembly process. Comparing the results of the metamodel-based and direct design optimization shows that MBDO allows finding a better solution using a three times smaller computational budget. In addition, analysis of the results obtained using stationary sampling data sets of different sizes highlighted the limitations of the employed sampling procedure. [ABSTRACT FROM AUTHOR]

The success of a product in the market is largely defined by the quality of design decisions made during the early stages of development. The product design requires designers to balance multiple objectives such as functionality, cost, and user satisfaction, while addressing the challenges posed by increasing product variants and customization demands. To tackle these challenges, one approach is to structure a comprehensive model that incorporates design for assembly (DFA) guidelines during the formulation of product architecture in the conceptual phase of development. While numerous strategies have been proposed in the literature, information is often scattered, making it difficult for readers to gain a comprehensive understanding of the topic. This paper systematically reviews the role and impact of DFA in product development, consolidating and presenting the information coherently. The review provides an overview of the methods developed, along with their potential benefits and limitations. A common framework is identified that defines the structure of the models, helping designers integrate assembly consideration into their design processes, thus reducing assembly time, cost, and complexity. The framework describes the operational setting, including the domain and context in which models operate, and offers a classification of possible methods and desired outputs. Additionally, the review identifies the industry in which case studies have been most frequently presented, and the software used to facilitate the process. By connecting with such a framework, future models can be created following a structured approach, and existing models can be classified and upgraded accordingly. [ABSTRACT FROM AUTHOR]

The mechanical properties of a commercially available hot-melt adhesive (HMA) have been studied under different environmental and loading conditions. To date, disassembly analyses including triggering features, design parameters, and time have not been fully investigated in the literature. In this study, experimental parametric studies have been performed on single lap joints considering the geometric features of the joint and a combination of thermo-mechanical effects. Disassembly time has been assessed through experimental analysis, considering variations in geometry, the use of alternative heat sources and different load conditions. Use of a heat gun as the heat source was found to lead to the highest variation in disassembly time compared to a static climatic chamber (i.e., industrial oven). In relation to the joint geometry, the disassembly time was mostly affected by the overlap length rather than the type or thickness of the base material. The outcomes of this study will drive the design of adhesive joints in mechanical applications, providing design-for-disassembly guidelines for the development of reversible joints employing hot-melt adhesives. [ABSTRACT FROM AUTHOR]

The Design for Assembly (DFA) method, incorporating lean and prefabricated construction concepts, is emerging as a novel approach to industrialize the construction industry. In recent years, several countries have developed guidance documents to enhance building assembly efficiency and quality through the implementation of DFA methods. However, there remains significant room for improvement in the assembly efficiency of prefabricated buildings, along with a lack of effective evaluation measures. Therefore, this paper aims to develop a DFA evaluation method specifically applicable to prefabricated buildings, utilizing the formula design, Delphi method, and Analytic Hierarchy Process (AHP) method. The DFA evaluation method presented in this study comprises two main components: the assembly efficiency index (AEI) and the assembly design index (ADI). The assembly efficiency evaluation serves to gauge the efficiency level of a construction system and identify the space for improvement. On the other hand, the assembly design evaluation identifies factors influencing assembly, enabling process enhancement and upgrading. Subsequently, the paper employs the developed evaluation method to analyze a case, the New Lawuga School in Yushu, China. The AEI of the New Lawuga School is 2.44 m3/pc., and the ADI value of the building is 0.54. The assembly evaluation of the New Lawuga School reveals that efficient assembly was achieved through integrated design and parts reduction. However, non-standardized design emerged as a hindrance to the assembly process. The primary contribution of this study lies in the proposed DFA evaluation method tailored specifically for prefabricated buildings. [ABSTRACT FROM AUTHOR]

This paper presents a new approach for searching the most favourable mechanical assembly sequence. The proposed method is described and its basic modules are presented. The concept is based on the assumption that the method should help the engineer in specifying the best assembly sequence with the short possible time calculation, taking into account the principles of design for assembly at an early stage of development of the product design. The algorithm for generating an accurate assembly sequence was described in detail and its application on real-life example was presented. [ABSTRACT FROM AUTHOR]

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There is a combinatorial explosion of alternative variants of an assembly design owing to the design freedom provided by additive manufacturing (AM). In this regard, a novel virtual reality-based decision-support framework is presented herein for extracting the superior assembly design to be fabricated by AM route. It specifically addresses the intersection between human assembly and AM hence combining design for assembly, and design for additive manufacturing using axiomatic design theory. Several virtual reality experiments were carried out to achieve this with human subjects assembling parts. At first, a two-dimensional table is assembled, and the data are used to confirm the independence of non-functional requirements such as assembly time and assembly displacement error according to independence axiom. Then this approach is demonstrated on an industrial lifeboat hook with three assembly design variations. The data from these experiments are utilized to evaluate the possible combinations of the assembly in terms of probability density based on the information axiom. The technique effectively identifies the assembly design most likely to fulfill the non-functional requirements. To the authors' best knowledge, this is the first study that numerically extracts the human aspect of design at an early design stage in the decision process and considers the selection of the superior assembly design in a detailed design stage. Finally, this process is automated using a graphical user interface, which embraces the practicality of the currently integrated framework and enables manufacturers to choose the best assembly design. [ABSTRACT FROM AUTHOR]

Topology optimization based on moving morphable components efficiently generates a topology that is expressed by a few geometrical design variables. However, conventional moving morphable components have three problems: lack of C¹ continuity between components, difficulty in describing a smooth rollup shape, and difficulty in generating a rigid joint to an optimized topology. In this study, a novel topology optimization framework was developed by introducing theories devised for multibody analysis. First, an adaptive moving morphable component based on absolute nodal coordinate formulation was proposed. Because both the position and gradient are used as design variables, C¹ continuity is ensured. Second, a position and gradient connection algorithm leveraging the linear constraint of the absolute nodal coordinate formulation was proposed to describe the smooth rollup shape. Third, a rigid joint was generated by introducing the gradient constraint equation in an optimizer. The developed framework exhibited superior convergence as compared with the conventional one in the benchmark short beam problem. It successfully generated an optimal topology with the intent of a designer (that is, designer-selected topology continuity and rigid joints), which facilitated the assembly and manufacturing of topologically optimized structural members to construct an entire aerospace structure. [ABSTRACT FROM AUTHOR]

The purpose of this research is to show the benefits to be obtained by redesigning production processes for small and mediumsized enterprises, which aim to grow but cannot develop due to runaway production. In this study, an exemplary approach is presented using the principles of Design for Assembly (DFA) in an enterprise aiming to grow in the elevator industry. Within the scope of the research, the doorframe assembly process of the semi-automatic elevator door, which is the most produced in the elevator industry, was examined. According to this; Design improvement studies were carried out in the assembly processes of the side profiles, head plate, forehead plate, floor plate and their subparts used in the production of the case. In the design improvement, the B&D design efficiency measurement principles were used. As a result of the improvements; The semi-automatic door frame, which is 98 pieces in its current design, has been reduced to 55 pieces with the new design. With the reduction in the number of parts and design changes, the total assembly time was reduced by 33.8% in assembly time. As a result of the improvements, the Design Efficiency has been increased from 8.5% to 12.8%. [ABSTRACT FROM AUTHOR]

In a contemporary era, Additive Manufacturing (AM), 3D printing or rapid prototyping has evolved as a distinctive method when compared with the traditional manufacturing. By addressing the topic of Design for Additive Manufacturing (DFAM), it is observed that the basic principles of DFAM and Design for Assembly (DFA) are well established and usually applicable on small-size AM parts. To address this critical manufacturing decision, our research work presents a new decision support system (DSS) for a large-size AM part which is based on compiling the existing DFAM methodologies. Before presenting the new DSS, the previous DFAM approaches are reviewed and investigated the research trends in part decomposition (PD), part consolidation (PC), and topology optimization (TO). The literature is categorized into six distinctive categories and among them the first phase is the information phase. Following this information requisite step, the next phase is parameter assessment phase and so on. The new DSS starts with the clarification of the design goal while in previous approaches this step was usually done at the later stages. Similarly, the remaining steps are efficiently integrated into the framework structure. The developed system is also guiding the post-decomposition assembly process. The developed DSS is validated using the case study of a 6-axis robotic arm. Moreover, a comprehensive concept for using the developed DSS framework is also presented in the research work. [ABSTRACT FROM AUTHOR]

The traditional clamping-sequence optimisation of sheet-metal parts requires many complicated finite element analyses, and clamping-sequence planning does not account for the springback from clamp-release. Therefore, this paper proposes a new optimisation method based on a heuristic algorithm. We first propose a new contact model of parts, clamps and supporting locators to analyse assembly deformation. Then, we use the distance between the actual and nominal positions to evaluate the clamp layout. Finally, we apply the heuristic algorithm to optimise the clamping sequence. We illustrate the proposed method with a case study of a taillight bracket, whose results show that the method of clamping-sequence optimisation can effectively decrease the deformation of sheet metal from clamping. [ABSTRACT FROM AUTHOR]

Design for Manufacturing, Assembly, and Disassembly is important in today's production systems because if this aspect is not considered, it could lead to inefficient operations and excessive material usage, both of which have a significant impact on manufacturing cost and time. Attention to this topic is important in achieving the target standards of Industry 4.0 which is inclusive of material utilisation, manufacturing operations, machine utilisation, features selection of the products, and development of suitable interfaces with information communication technologies (ICT) and other evolving technologies. Design for manufacturing (DFM) and Design for Assembly (DFA) have been around since the 1980's for rectifying and overcoming the difficulties and waste related to the manufacturing as well as assembly at the design stage. Furthermore, this domain includes a decision support system and knowledge base with manufacturing and design guidelines following the adoption of ICT. With this in mind, 'Design for manufacturing and assembly/disassembly: Joint design of products and production systems', a special issue has been conceived and its contents are elaborated in detail. In this paper, a background of the topics pertaining to DFM, DFA and related topics seen in today's manufacturing systems are discussed. The accepted papers of this issue are categorised in multiple sections and their significant features are outlined. [ABSTRACT FROM AUTHOR]

Three-dimensional spatial packaging of interconnected systems with physical interactions (SPI2) design plays a vital role in the functionality, operation, energy usage, and life cycle of practically all engineered systems, from chips to ships. SPI2 design problems are highly nonlinear, involving tightly constrained component placement, governed by coupled physical phenomena (thermal, hydraulic, electromagnetic, etc.), and involve energy and material transfer through intricate geometric interconnects. While many aspects of engineering system design have advanced rapidly in the last few decades through breakthroughs in computational support, SPI2 design has largely resisted automation and in practice requires at least some human-executed design steps. SPI2 system reasoning and design decisions can quickly exceed human cognitive abilities at even moderate complexity levels, thwarting efforts to accelerate design cycles and tackle increasingly complex systems. Existing design methods treat pieces of the SPI2 problem separately without a fundamental systems approach, are sometimes inefficient to evaluate various possible designs, and present barriers to effective adoption in practice. This article explores a vision of a holistic SPI2 design approach needed to develop next-generation automated design methods capable of rapidly producing viable SPI2 design candidates. We review several technical domains related to holistic SPI2 design, discuss existing knowledge gaps and practical challenges, examine exciting opportunities at the intersection of multiple domains that can enable comprehensive exploration of SPI2 design spaces, and present one viable two-stage SPI2 design automation framework. Holistic SPI2 design opens up a new direction of high industrial and societal relevance for the design research community. [ABSTRACT FROM AUTHOR]

The Design for Assembly (DFA) method, incorporating lean and prefabricated construction concepts, is emerging as a novel approach to industrialize the construction industry. In recent years, several countries have developed guidance documents to enhance building assembly efficiency and quality through the implementation of DFA methods. However, there remains significant room for improvement in the assembly efficiency of prefabricated buildings, along with a lack of effective evaluation measures. Therefore, this paper aims to develop a DFA evaluation method specifically applicable to prefabricated buildings, utilizing the formula design, Delphi method, and Analytic Hierarchy Process (AHP) method. The DFA evaluation method presented in this study comprises two main components: the assembly efficiency index (AEI) and the assembly design index (ADI). The assembly efficiency evaluation serves to gauge the efficiency level of a construction system and identify the space for improvement. On the other hand, the assembly design evaluation identifies factors influencing assembly, enabling process enhancement and upgrading. Subsequently, the paper employs the developed evaluation method to analyze a case, the New Lawuga School in Yushu, China. The AEI of the New Lawuga School is 2.44 m3/pc., and the ADI value of the building is 0.54. The assembly evaluation of the New Lawuga School reveals that efficient assembly was achieved through integrated design and parts reduction. However, non-standardized design emerged as a hindrance to the assembly process. The primary contribution of this study lies in the proposed DFA evaluation method tailored specifically for prefabricated buildings.

Planning the shortest collision-free path among scattered obstacles is an NP-complete problem. As reviewed in this paper, a variety of deterministic as well as heuristic methods have been developed to address different instances of the problem. The focus of the deterministic methods is primarily on the optimality of the final solution and has been applied exclusively to regular shapes such as spheres or cubes. Nevertheless, due to the problem's intrinsic complexities (especially in 3D), researchers mainly resort to heuristics that offer acceptable (yet possibly suboptimal) solutions with reasonable resources. Therefore, less attention has been given to further the state-of-the-art in deterministic methods, which for 3D problems primarily focuses on approximating the solution. However, with the advancements in high-performance computing, we believe it is time to focus on solution quality. As such, this study aims to further the efforts in deterministic optimization methods for 3D path planning by overcoming some challenges of the existing methods and improving the optimality of the solution. The proposed approach is rooted in visibility-based planning methods where the obstacle-free space is modeled as a connectivity graph to be searched for the shortest path. The advantage of the proposed method in constructing the representative graph is that it does not make approximations to identify the graph nodes, unlike the existing methods. Nor does it limit the objects' geometries to specific shapes such as blocks or spheres. The capability of the method in finding the shortest collision-free paths in environments cluttered with convex polyhedra is demonstrated using sample test problems. [ABSTRACT FROM AUTHOR]

A major challenge for manufacturing companies today is to manage a huge amount of product variants and build options at the same time in manufacturing engineering and in production. The overall complexity and risk of quality errors in manual assembly will increase placing high demands on the operators who must manage many different tasks in current production. Therefore, methods for decreasing and controlling assembly complexity are urgent because managing complex product and installation conditions will result in distinct competitive advantages. The objective of this paper is to present a method for predictive assessment of basic manual assembly complexity and explain how included complexity criteria were arrived at. The verified method includes 16 high complexity and 16 low complexity criteria to aid designers in preventing costly errors during assembly and create good basic assembly conditions in early design phases of new manufacturing concepts. [ABSTRACT FROM AUTHOR]

The design for manufacturing and assembly (DFMA) is a family of methods belonging to the design for X (DfX) category which goal is to optimize the manufacturing and assembly phase of products. DFMA methods have been developed at the beginning of the 1980s and widely used in both academia and industries since then. However, to the best of the authors' knowledge, no systematic literature reviews or mapping has been proposed yet in the field of mechanical design. The goal of this paper is to provide a systematic review of DFMA methods applied to mechanical and electro-mechanical products with the aim to collect, analyse, and summarize the knowledge acquired until today and identify future research areas. The paper provides an overview of the DFMA topic in the last four decades (i.e., from 1980 to 2021) emphasizing operational perspectives such as the design phase in which methods are used, the type of products analysed, the adoption of quantitative or qualitative metrics, the tool adopted for the assessment, and the technologies involved. As a result, the paper addresses several aspects associated with the DFMA and different outcomes retrieved by the literature review have been highlighted. The first one concerns the fact that most of the DFMA methods have been used to analyse simple products made of few components (i.e., easy to manage with a short lead-time). Another important result is the lack of valuable DFMA methods applicable at early design phases (i.e., conceptual design) when information is not detailed and presents more qualitative than quantitative data. Both results lead to the evidence that the definition of a general DFMA method and metric adaptable for every type of product and/or design phase is a challenging goal that presents several issues. Finally, a bibliographic map was developed as a suitable tool to visualize results and identify future research trends on this topic. From the bibliometric analysis, it has been shown that the overall interest in DFMA methodologies decreased in the last decade. [ABSTRACT FROM AUTHOR]

This study presents the integrating of the DFA concept for the ASP problem to reduce the cost and time of assembling the product. Enhanced Fruit Fly algorithm is developed by incorporating the range of angles to the fruit fly during the initial fly as compared with the random angle selected in the general fruit fly algorithm to generate optimal assembly sequences. The fitness equation is formulated with directional feasibility data to engender optimal assembly sequences. The proposed concept is applied to the pen and motor drive assembly to test the performance of the algorithm. The results from the proposed notion are compared with the GA, ACO, FPA, and IHS for the motor drive assembly in terms of the number of levels of the assembly sequence, fitness value, number of iterations, and number of optimal sequences generated. [ABSTRACT FROM AUTHOR]

In this paper, an assembly sequence planning system, based on artificial neural networks, is developed. The problem of artificial neural network itself is largely related to symmetry at every stage of its creation. A new modeling scheme, known as artificial neural networks, takes into account selected DFA (Design for Assembly) rating factors, which allow the evaluation of assembly sequences, what are the input data to the network learning and then estimate the assembly time. The input to the assembly neural network procedure is the sequences for assembling the parts, extended by the assembly's connection graph that represents the parts and relations between these parts. The operation of a neural network is to predict the assembly time based on the training dataset and indicate it as an output value. The network inputs are data based on selected DFA factors influencing the assembly time. The proposed neural network model outperforms the available assembly sequence planning model in predicting the optimum assembly time for the mechanical parts. In the neural networks, the BFGS (the Broyden–Fletcher–Goldfarb–Shanno algorithm), steepest descent and gradient scaling algorithms are used. The network efficiency was checked from a set of 20,000 test networks with randomly selected parameters: activation functions (linear, logistic, tanh, exponential and sine), the number of hidden neurons, percentage set of training and test dataset. The novelty of the article is therefore the use of parts of the DFA methodology and the neural network to estimate assembly time, under specific production conditions. This approach allows, according to the authors, to estimate which mechanical assembly sequence is the most advantageous, because the simulation results suggest that the neural predictor can be used as a predictor for an assembly sequence planning system. [ABSTRACT FROM AUTHOR]

Today, most companies do not consider the assembly aspects of a product until late in the design process, and often do so in a manual way, mainly relying on the experience of the assembly engineers. This results in designs that comply with the performance requirements, but that have a suboptimal or unfeasible assembly process. This leads to design changes late in the product development process, causing significant extra costs. To solve this issue, a framework is presented, which is able to perform design optimizations considering both the assembly process and the performance of the future product, allowing trade-off analysis of the obtained solutions. The assembly process evaluation is automated with an algorithm that evaluates Design For Assembly (DFA) rules, enabling the assessment and quantitative evaluation of the ease-of-assembly of the whole product and/or individual assembly operations. The presented framework is used in the context of the design of a gearbox, in which total mass, assemblability and performance need to be optimized. The performance of the gearbox is determined by the axle's stiffness and first resonance frequency. The assemblability of the gearbox is evaluated based on 2 DFA rules. The first rule considers the number of unique types of standard parts used in the assembly and how they influence the complexity of the assembly process. The second rule evaluates the convenience of fastening standard parts (e.g., bolts or screws) using the corresponding tool during the assembly operation. First, the design problem is formulated as a single objective optimization in which mass and assemblability are optimized given constraints on the axle's stiffness and first resonance frequency. In each iteration of the optimization, a parametrized finite element model is used for the performance evaluation of the current design, while the assemblability cost estimation is based on the CAD model of the assembly. Second, a multi-objective co-optimization of the gearbox design is carried out were both performance and assemblability are optimized. By constructing the Pareto front an accurate and effective trade-off can be made between objectives of the gearbox design, which allows to reasonably choose the best design of the gearbox. [ABSTRACT FROM AUTHOR]

The components of complex systems such as automobiles or ships communicate via connectors, including wires, hoses, or pipes whose weight could substantially increase the total weight of the system. Hence, it is of paramount importance to lay out these connectors such that their overall weight is minimized. In this paper, a computationally efficient approach is proposed to optimize the layout of flexible connectors (e.g., cable harnesses) by minimizing their overall length while maximizing their common length. The approach provides a framework to mathematically model the cable harness layout optimization problem. A Multiobjective Genetic Algorithm (MOGA) solver is then applied to solve the optimization problem, which outputs a set of non-dominated solutions to the bi-objective problem. Finally, the effects of the workspace's geometric structure on the optimal layouts of cable harnesses are discussed using sample test cases. The overarching objective of this study is to provide insight for designers of cable harnesses when deciding on the final layout of connectors considering aspects such as accessibility to and maintainability of these connectors. [ABSTRACT FROM AUTHOR]

Manufacturing firms are facing the challenge of minimizing variety-induced complexity in assembly systems. One of the effective approaches to complexity management is to reconfigure the assembly system by rearranging its assembly sequence. In order to rearrange an assembly sequence, a design-oriented approach is necessary because assembly is an activity of connecting parts through an interface between them. It means that the assembly sequence in production is restricted by the structure of interface connections in design. In this vein, this paper introduces a new design-oriented approach called interface design approach to complexity management in assembly systems. First, the mechanism of how the structure of interface connections affects assembly system complexity is identified. Then, an interface design framework is proposed for effectively finding an optimal interface structure and its assembly sequence to minimize assembly system complexity. For evaluating the complexity, the operator choice complexity index is adopted and modified for the interface design problem. In the case study, the framework is applied to the interface design problem by using industrial data of a plasma display panel (PDP) family from LG Electronics. The result of the study demonstrates that the assembly system complexity is significantly reduced by the proposed interface design framework.

Due to the current and highly competitive industrial scenario, the technology-oriented organizations have been making routine adjustments to the conventional IPDP, in order to seek more profitable business models. Identifying the product functions, as well as its importance - perceived by the consumer - and being able to associate this information with manufacturability and assembly aspects, is fundamental to achieve more competitive, low-cost and higher quality products. This article objective is to evaluate this method concept, applying it in an industrial project. In order to assess the method within the complete integrated product development process (IPDP), the activities related to the conceptual and preliminary phases of the project delineated this article limits. This study selected a subgroup of the white goods industry, where first the traditional models of VE were applied in the conceptual design phase. Subsequently, the classic DFA models were applied in the preliminary design phase. Thus, it was possible to apply the proposed iterative method, where the alternatives generated with the DFA were cyclically re-evaluated, function by function, in the previous stage of value analysis. With this, this study came to the method assessment, its gains and limitations. Then, the original design was compared with the solution after the proposal application, without the method used. Finally, this study verified the influence of the method on the balance between the value and the cost of each function, in addition to the direct comparison of the solution final cost with the version without the method application. Among the results, this article presents a report showing the method viability, its particularities, impacts, and limitations. [ABSTRACT FROM AUTHOR]

The assembly precision of wheel alignment parameters is vital to vehicle handling stability. Due to the vertical wheel displacement and compliant components in suspension systems, it is difficult to assemble qualified vehicles with proper wheel alignment parameters. In the assembly shop of the automobile factory, the adjustment of wheel alignment parameters is the most time-consuming process because it relies on trial and error. In order to provide a theoretical guidance to the precision control of wheel alignment parameters, this paper extends the theory of equilibrium equations of incremental forces (EEIF) to 3D compliant mechanisms. Constraint equations of kinematic joints are adopted to express the spatial relationships of different parts. A couple of fixed and floating joint coordinate systems (CSs) are used together to represent deviations of compliant components. The impacts of suspension part deviations on vertical wheel displacement and assembly deformations are well illustrated by such approach. Accuracy of the proposed method is verified by comparing with ADAMS simulation. The results show that the error rates of the 3D EEIF method are less than 5%. Furthermore, statistical assembly variation analysis of a Macpherson suspension is accomplished by using the proposed method and an optimized process strategy is put forward. [ABSTRACT FROM AUTHOR]