A Part Consolidation Design Method for Additive Manufacturing based on Product Disassembly Complexity

Kim S., Rosen D.W., Witherell P., Ko H.

Design for additive manufacturing (DFAM) provides design freedom for creating complex geometries and guides designers to ensure the manufacturability of parts fabricated using additive manufacturing (AM) processes. However, there is a lack of formalized DFAM knowledge that provides information on how to design parts and how to plan AM processes for achieving target goals. Furthermore, the wide variety of AM processes, materials, and machines creates challenges in determining manufacturability constraints. Therefore, this study presents a DFAM ontology using the web ontology language (OWL) to semantically model DFAM knowledge and retrieve that knowledge. The goal of the proposed DFAM ontology is to provide a structure for information on part design, AM processes, and AM capability to represent design rules. Furthermore, the manufacturing feature concept is introduced to indicate design features that are considerably constrained by given AM processes. After developing the DFAM ontology, queries based on design rules are represented to explicitly retrieve DFAM knowledge and analyze manufacturability using Semantic Query-enhanced Web Rule Language (SQWRL). The SQWRL rules enable effective reasoning to evaluate design features against manufacturing constraints. The usefulness of the DFAM ontology is demonstrated in a case study where design features of a bracket are selected as manufacturing features based on a rule development process. This study contributes to developing a reusable and upgradable knowledge base that can be used to perform manufacturing analysis.

Yang S., Talekar T., Sulthan M.A., Zhao Y.F.

Part consolidation (PC) is one of the effective ways to simplify product structure. Through part consolidation, it is expected to reduce weight and size, minimize assembly operation, improve performance, and prolong service life. As additive manufacturing (AM) evolves into an end-of-use product manufacturing process, the possibility of part consolidation has further increased. However, the life-cycle sustainability aspect related to PC with AM is rarely known. To support design for environment, this paper proposes a framework to systematically investigate the environmental impact of PC on production, service, and end-of-life (EoL) activities. In this framework, generic quantitative models for PC-related sustainability assessment of these life-cycle stages are presented from an incremental perspective. In each model, change in sustainability indices are calculated with respect to the change propagated from the design change (PC) when PC is achieved. From the model, consolidated design shows definite promise at assembly and service stage; however, there is still uncertainty in deciding the sustainability benefit at manufacturing and EoL stage. In this paper, a case study with a redesigned floor attachment in a train is exemplified and binder jetting (BJ) AM process is chosen as the default manufacturing process. Due to the lack of data of EoL and minor effect on maintenance as well as fuel economy, only the environmental impact on production is analyzed. The result reveals two important implications: 1) consolidated design shows significant promise in reducing energy consumption and environmental impact (average 20%), but it results in an increase of health toxicity level; 2) reduction of environmental impact (up limit 13.2%) at assembly stage is not obvious. In the end, important conclusions and future research are outlined.

Dinar M., Rosen D.W.

Design for additive manufacturing (DFAM) gives designers new freedoms to create complex geometries and combine parts into one. However, it has its own limitations, and more importantly, requires a shift in thinking from traditional design for subtractive manufacturing. There is a lack of formal and structured guidelines, especially for novice designers. To formalize knowledge of DFAM, we have developed an ontology using formal web ontology language (OWL)/resource description framework (RDF) representations in the Protégé tool. The description logic formalism facilitates expressing domain knowledge as well as capturing information from benchmark studies. This is demonstrated in a case study with three design features: revolute joint, threaded assembly (screw connection), and slider–crank. How multiple instances (build events) are stored and retrieved in the knowledge base is discussed in light of modeling requirements for the DFAM knowledge base: knowledge capture and reuse, supporting a tutoring system, integration into cad tools. A set of competency questions are described to evaluate knowledge retrieval. Examples are given with SPARQL queries. Reasoning with semantic web rule language (SWRL) is exemplified for manufacturability analysis. Knowledge documentation is the main objective of the current ontology. However, description logic creates multiple opportunities for future work, including representing and reasoning about DFAM rules in a structured modular hierarchy, discovering new rules with induction, and recognizing patterns with classification, e.g., what leads to “successful” versus “unsuccessful” fabrications.

Lei N., Yao X., Moon S.K., Bi G.

ABSTRACTAdditive manufacturing (AM) is projected to have a profound impact on mass customisation. In order to benefit from this new technology, we need to incorporate AM into design processes. This paper addresses that need by introducing an AM process model for product family design. The proposed model reflects the ability of AM to produce customised and complex parts without tooling efforts. By utilising AM, we eliminate all constraints which arise in conventional product family designs from finding a compromise between commonality and performance. The proposed model starts by identifying design requirements and constraints. Subsequently, we use topology optimisation to determine an optimal design for each product. Next, finite element analysis and cost analysis are performed. We combine the analysis results in one three-dimensional plot, which displays the merits of the individual component realisations. Thus, a fair and competitive component evaluation is possible and the most suitable product family ...

Kim S., Moon S.K.

In order to improve the efficiency of disassembly and product recovery of an abandoned product at the end-of-life stage, it is essential to develop modular product architecture by considering manufacturing and recovering processes in early product design stage. In this paper, a novel concept of a design methodology is introduced to develop eco-modular product architecture and assess the modularity of the architecture from the viewpoint of product recovery. Eco-modular product architecture contributes to enhancing product recovery processes by recycling and reusing modules without full disassembly at component or material levels. It leads to less consumption of natural resources and less landfill damage to the environment. Three sustainable modular drivers, namely, interface complexity, material similarity, and lifespan similarity, are introduced to reconstruct the modular architecture of commercial products into the eco-modular architecture. Alternatives of modular architectures are identified by Markov Cluster Algorithm based on these sustainable modular drivers and physical interconnections of the components of product architecture. To select the eco-modular architecture from these alternatives, we propose modularity assessment metrics to identify independent interactions between modules and the degrees of similarity within each module. To demonstrate the effectiveness of the proposed methodology, a case study is performed with a coffee maker.

Thompson M.K., Moroni G., Vaneker T., Fadel G., Campbell R.I., Gibson I., Bernard A., Schulz J., Graf P., Ahuja B., Martina F.

The past few decades have seen substantial growth in Additive Manufacturing (AM) technologies. However, this growth has mainly been process-driven. The evolution of engineering design to take advantage of the possibilities afforded by AM and to manage the constraints associated with the technology has lagged behind. This paper presents the major opportunities, constraints, and economic considerations for Design for Additive Manufacturing. It explores issues related to design and redesign for direct and indirect AM production. It also highlights key industrial applications, outlines future challenges, and identifies promising directions for research and the exploitation of AM's full potential in industry.

Otto K., Hölttä-Otto K., Simpson T.W., Krause D., Ripperda S., Ki Moon S.

Modular product platforms have been shown to provide substantial cost and time savings while still allowing companies to offer a variety of products. As a result, a multitude of product platform methods have been developed over the last decade within the design research community. However, comparison and integration of suitable methods is difficult since the methods have, for the most part, been developed in isolation from one another. In reviewing the literature in modularity and product platforms, we create a generic set of 13 platform design steps for developing a platform concept. We then examine a set of product platform concept development processes used at several different companies, and from this form a generic sequence of the steps. We then associate the various developed methods to the sequence, thereby enabling the chaining together of the various modular and platform design methods developed by the community.

Tang Y., Zhao Y.F.

Purpose This paper aims to provide a comprehensive review of the state-of–the-art design methods for additive manufacturing (AM) technologies to improve functional performance. Design/methodology/approach In this survey, design methods for AM to improve functional performance are divided into two main groups. They are design methods for a specific objective and general design methods. Design methods in the first group primarily focus on the improvement of functional performance, while the second group also takes other important factors such as manufacturability and cost into consideration with a more general framework. Design methods in each groups are carefully reviewed with discussion and comparison. Findings The advantages and disadvantages of different design methods for AM are discussed in this paper. Some general issues of existing methods are summarized below: most existing design methods only focus on a single design scale with a single function; few product-level design methods are available for both products’ functionality and assembly; and some existing design methods are hard to implement for the lack of suitable computer-aided design software. Practical implications This study is a useful source for designers to select an appropriate design method to take full advantage of AM. Originality/value In this survey, a novel classification method is used to categorize existing design methods for AM. Based on this classification method, a comprehensive review is provided in this paper as an informative source for designers and researchers working in this field.

Liu J.

ABSTRACTThis paper makes a comparative study about the structural performances of the consolidated AM (additive manufacturing) parts and the multi-piece assemblies. Generally, it is recognised that AM part consolidation can improve the structural performance compared to the traditional multi-piece assembly. However, this may not be true given that the AM materials are directionally weakened, especially in the build direction (BD). Hence, the comparative study performed in this work will provide some conclusions and at the same time, these conclusions could be valuable guidelines for designing AM part consolidation. For implementation details, the level set topology optimisation method will be applied to optimising the multi-piece assembly with rigid joints and the AM part with weakened material properties; and the same design domain will be shared in order to make a fair comparison. A set of different joint positions and material weakening levels will be studied in order to get comprehensive conclusions.

Lei X., Wang F., Wu F., Zhang A., Pedrycz W.

Markov clustering (MCL) is a commonly used algorithm for clustering networks in bioinformatics. It shows good performance in clustering dynamic protein-protein interaction networks (DPINs). However, a limitation of MCL and its variants (e.g, regularized MCL and soft regularized MCL) is that the clustering results are mostly dependent on the parameters whose values are user-specified. In this study, we propose a new MCL method based on the firefly algorithm (FA) to identify protein complexes from DPIN. Based on three-sigma principle, we construct the DPIN and discuss an overall modeling process. In order to optimize parameters, we exploit a number of population-based optimization methods. A thorough comparison completed for different swarm optimization algorithms such as particle swarm optimization (PSO) and firefly algorithm (FA) has been carried out. The identified protein complexes on the DIP dataset show that the new algorithm outperforms the state-of-the-art approaches in terms of accuracy of protein complex identification.

Yao X., Moon S.K., Bi G.

Additive manufacturing (AM) has evolved from prototyping to functional part fabrication for a wide range of applications. Challenges exist in developing new product design methodologies to utilize AM-enabled design freedoms while limiting costs at the same time. When major design changes are made to a part, undesired high cost increments may be incurred due to significant adjustments of AM process settings. In this research, we introduce the concept of an additive manufactured variable product platform and its associated process setting platform. Design and process setting adjustments based on a reference part are constrained within a bounded feasible space (FS) in order to limit cost increments. In this paper, we develop a cost-driven design methodology for product families implemented with additive manufactured variable platforms. A fuzzy time-driven activity-based costing (FTDABC) approach is introduced to estimate AM production costs based on process settings. Time equations in the FTDABC are computed in a trained adaptive neuro-fuzzy inference system (ANFIS). The process setting adjustment's FS boundary is identified by solving a multi-objective optimization problem. Variable platform design parameter limitations are computed in a Mamdani-type expert system, and then used as constraints in the design optimization to maximize customer perceived utility. Case studies on designing an R/C racing car family illustrate the proposed methodology and demonstrate that the optimized additive manufactured variable platforms can improve product performances at lower costs than conventional consistent platform-based design.

Gao W., Zhang Y., Ramanujan D., Ramani K., Chen Y., Williams C.B., Wang C.C., Shin Y.C., Zhang S., Zavattieri P.D.

Additive manufacturing (AM) is poised to bring about a revolution in the way products are designed, manufactured, and distributed to end users. This technology has gained significant academic as well as industry interest due to its ability to create complex geometries with customizable material properties. AM has also inspired the development of the maker movement by democratizing design and manufacturing. Due to the rapid proliferation of a wide variety of technologies associated with AM, there is a lack of a comprehensive set of design principles, manufacturing guidelines, and standardization of best practices. These challenges are compounded by the fact that advancements in multiple technologies (for example materials processing, topology optimization) generate a positive feedback loop effect in advancing AM. In order to advance research interest and investment in AM technologies, some fundamental questions and trends about the dependencies existing in these avenues need highlighting. The goal of our review paper is to organize this body of knowledge surrounding AM, and present current barriers, findings, and future trends significantly to the researchers. We also discuss fundamental attributes of AM processes, evolution of the AM industry, and the affordances enabled by the emergence of AM in a variety of areas such as geometry processing, material design, and education. We conclude our paper by pointing out future directions such as the print-it-all paradigm, that have the potential to re-imagine current research and spawn completely new avenues for exploration. The fundamental attributes and challenges/barriers of Additive Manufacturing (AM).The evolution of research on AM with a focus on engineering capabilities.The affordances enabled by AM such as geometry, material and tools design.The developments in industry, intellectual property, and education-related aspects.The important future trends of AM technologies.

Yang S., Tang Y., Zhao Y.F.

As additive manufacturing (AM) evolves from Rapid Prototyping (RP) to the end-of-use product manufacturing process, manufacturing constraints have been largely alleviated and design freedom for part consolidation is extremely broadened. AM enabled part consolidation method promises a more effective way to achieve part count reduction and the ease of assembly compared with traditional Design for Manufacture and Assembly (DFMA) method. However, how to achieve AM enabled part consolidation is not well developed. In this paper, a new part consolidation method comprehensively considering function integration and structure optimization is proposed. This presented method is characterized by two main modules. The first one is to achieve better functionality through surface-level function integration and sequential part-level function integration based on design specifications with an initial CAD model which is designed for conventional manufacturing process. The other module is to realize better performance through the introduction and optimization of heterogeneous lattice structures according to performance requirements. The proposed part consolidation method highlights itself from the perspective of functionality achievement and performance improvement. An example of a triple clamp is studied to verify the effectiveness of the proposed model. The optimized results show that the part count has been reduced from 19 to 7 with a less weight by 20% and demonstrates better performance.

Soh S.L., Ong S.K., Nee A.Y.

With the emphasis on environmental sustainability, remanufacturing has become a major aspect of life cycle engineering with the intention to bring a product or part back to its useful life. In order to retrieve essential elements within a product for remanufacturing, disassembly is a necessary process to begin with. Increasing the efficiency for disassembly can be feasible if the disassembly perspective is taken into consideration during the product design stage. Design for disassembly (DFD) guidelines have been established to provide suggestions to product designers on the various design considerations that could be incorporated to aid disassembly. However, these guidelines may be difficult to implement due to the conflicting issues found within a product itself. A conceptual framework based on practical considerations is proposed to aid the product designer in prioritising the relevant DFD guidelines that could be used to increase the efficiency of retrieving a high value core of a product for remanufacturing.

Yang S., Zhao Y.F.

As additive manufacturing (AM) process evolves from rapid prototyping to the end-of-use product manufacturing process, manufacturing constraints have largely been alleviated and design freedom has been significantly broadened, including shape complexity, material complexity, hierarchical complexity, and functional complexity. Inevitably, conventional Design Theory and Methodology (DTM) especially life-cycle objectives oriented ones are challenged. In this paper, firstly, the impact of AM on conventional DTM is analyzed in terms of design for manufacturing (DFM), design for assembly (DFA), and design for performance (DFP). Abundance of evidences indicate that conventional DTM is not qualified to embrace these new opportunities and consequently underline the need for a set of design principles for AM to achieve a better design. Secondly, design methods related with AM are reviewed and classified into three main groups, including design guidelines, modified DTM for AM, and design for additive manufacturing (DFAM). The principles and representative design methods in each category are studied comprehensively with respect to benefits and drawbacks. A new design method partially overcoming these drawbacks by integrating function integration and structure optimization to realize less part count and better performance is discussed. Design tools as a necessary part for supporting design are also studied. In the meantime, the review also identified the possible areas for future research.

Ko M., Yoon Y., Kim J., Kim S., Kwon S.

Radhakrishnan J., Singh G., Kumar P., Nayan N., Ramamurty U.

Ye L.

Abstract This paper comprehensively discusses the core applications and innovation strategies of 
CAD/CAM technology in mechanical parts manufacturing, with a special focus on automatic 
path planning, CNC programming, multi-axis and high-speed machining technology, as well 
as intelligent upgrading of quality control and production management. By introducing 
advanced models such as Deep Graph Neural Reinforcement Learning Path Planner (DGNet RPP), it demonstrates how to utilize the fusion of Deep Reinforcement Learning and Graph
Neural Network to adaptively optimize the tool path planning of complex parts to ensure 
machining efficiency and accuracy. Meanwhile, the importance of optimization and post processing techniques for NC programming, such as simulated annealing and ant colony 
optimization, is emphasized to improve machining efficiency and code adaptability. The 
implementation of multi-axis machining and high-speed machining technology has greatly 
promoted the progress of complex parts machining accuracy and surface quality, especially in 
high-end manufacturing fields such as aerospace. In addition, the article also explains the key 
role of CAM systems in quality control and production scheduling, how to ensure the quality 
of parts through real-time monitoring and data analysis, as well as through advanced planning 
and scheduling to optimize the production process, reduce costs, and improve market 
responsiveness.

Kim S., Tang Y., Park S., Rosen D.W.

Redesigning existing parts is challenging without keen insights into capabilities afforded by AM and with the absence of systematic design methods for the early product design stage. Therefore, this study proposes a systematic design method to leverage fully AM design benefits for reconceptualizing product architecture, which leads to consolidate parts and simplify product architecture. The proposed design method consists of four steps to achieve the goal. First, a baseline product architecture should be identified as a starting point of reconceptualization. Second, candidates for reconceptualization are identified by design principles for AM. Third, AM design benefits are recommended by the developed knowledgebase and query language, which can replace functions of the candidates. AM design benefits are applied to reconceptualize existing part design and lead to more efficient product architectures. Lastly, the reconceptualized product architecture is evaluated. To demonstrate usefulness of the proposed method, a case study is performed on an electric motorcycle.

Fan H., Hu J., Wang Y., Zhang H., Guo W., Li J., Xu S., Li H., Liu P.

Laser Additive Manufacturing (LAM) is a promising rapid prototyping technique that is commonly used in aerospace and other areas due to its ability to manufacture complex structures quickly. Aluminum alloys have low density, high specific strength, and superior corrosion resistance, making them suitable for a wide range of applications. However, aluminum alloys have high laser reflectivity and thermal conductivity, easily oxidation and a high tendency for hot fractures and pores, making it difficult to obtain LAMed aluminum alloy. Furthermore, it is important to find an optimized laser processing method to obtain high quality (good microstructure and mechanical properties) LAMed aluminum structure. To address the aforementioned issues, as well as the current research status of LAMed aluminum alloys, this paper summarizes the microstructure and mechanical properties of aluminum alloys fabricated by various LAM technologies. The focus is on process application and technical characterization, as well as the issues of improving cracks and pores through different process parameters and post heat treatment. The text discusses the basic concept of aluminum alloys and the principles of some typical LAM processes. It also reviews recent research progress on microstructural characterization, strengthening mechanism evaluation, post heat treatment processes, and nanoparticle strengthening mechanisms. The aim is to establish a preliminary comprehensive relationship between LAM processes, microstructures, and mechanical properties. Finally, in conclusion, this paper forecasts the future development trends of LAMed aluminum alloys.

Priyadarshini J., Singh R.K., Mishra R., He Q., Braganza A.

AbstractThis study addresses the paradoxical tensions that arise during additive manufacturing (AM) implementation for circular economy goals in the healthcare sector. Using the lens of paradox theory, this study identifies four competing priorities that stakeholders may encounter while adopting AM. Focus group discussions among 12 industry experts from the healthcare supply chain were conducted to verify the paradoxes. Semi-structured interviews were then conducted with 10 industry experts to derive the solutions to manage these tensions from an Industry 5.0 perspective to achieve the full benefits of AM. This study expands paradox theory into the AM literature and provides a novel ‘both/and’ perspective (i.e. a pluralistic rather than a dualistic perspective) to look at emerging tensions encountered while implementing AM in the healthcare sector. This perspective will help decision-makers realise that these tensions can be managed over time to turn them into creative, rather than destructive, forces.

Joshua R.J., Raj S.A., Hameed Sultan M.T., Łukaszewicz A., Józwik J., Oksiuta Z., Dziedzic K., Tofil A., Shahar F.S.

Precision manufacturing requirements are the key to ensuring the quality and reliability of biomedical implants. The powder bed fusion (PBF) technique offers a promising solution, enabling the creation of complex, patient-specific implants with a high degree of precision. This technology is revolutionizing the biomedical industry, paving the way for a new era of personalized medicine. This review explores and details powder bed fusion 3D printing and its application in the biomedical field. It begins with an introduction to the powder bed fusion 3D-printing technology and its various classifications. Later, it analyzes the numerous fields in which powder bed fusion 3D printing has been successfully deployed where precision components are required, including the fabrication of personalized implants and scaffolds for tissue engineering. This review also discusses the potential advantages and limitations for using the powder bed fusion 3D-printing technology in terms of precision, customization, and cost effectiveness. In addition, it highlights the current challenges and prospects of the powder bed fusion 3D-printing technology. This work offers valuable insights for researchers engaged in the field, aiming to contribute to the advancement of the powder bed fusion 3D-printing technology in the context of precision manufacturing for biomedical applications.

Zheng H., Guo H., Pang T., Guo Z., Guo X.

AbstractIn response to the problem that it is easy to fall into local optimum when using the traditional clustering algorithm to divide the modules, this paper improves the initialisation strategy of the NSGA2 algorithm and combines it with the FCM algorithm to propose an improved NSGA2-FCM algorithm for clustering analysis. Firstly, the FBS mapping is used to model the functional structure of the product system and identify the relationship between the product functional structures. Secondly, a correlation synthesis matrix is constructed based on the relationships between the module division drivers. Finally, the improved NSGA2-FCM algorithm is applied to cluster analysis of the product to derive the best module division scheme. The algorithm avoids falling into local optima by optimising the initialisation strategy of the NSGA2 algorithm, while using the FCM algorithm to improve the accuracy of the clustering. This allows the algorithm to explore the solution space more effectively when finding the best module partitioning solution. Finally, the effectiveness of the algorithm for module classification of light industrial equipment is verified using beer fermenters as a case study.

Hui Z., Hanwen G., Tonglin P., Zijian G., Xiao G.

Abstract To solve the problem that the traditional clustering algorithm tends to fall into local optimum when dividing modules, the initialization strategy of NSGA2 algorithm is improved, and an improved NSGA2-FCM algorithm is proposed for clustering analysis in combination with FCM algorithm. First, FBS mapping is used to model the functional structure of the product system and identify the relationship between the functional structures of the product. Secondly, the relevant synthesis matrix is constructed based on the relationship between the driving factors of module division, and finally, the improved NSGA2-FCM algorithm is used to cluster the product to arrive at the best module division solution. The paper concludes with a case study of a beer fermenter to verify the effectiveness of the algorithm for modular classification of light industrial equipment.

Auyeskhan U., Alex C.S., Park S., Kim D., Jung I.D., Kim N.

Abstract There is a combinatorial explosion of alternative variants of an assembly design owing to the design freedom provided by Additive Manufacturing. 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 2D table is assembled, and the data are used to confirm the independence of nonfunctional 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 nonfunctional 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.

Hocker S.J., Richter B., Spaeth P.W., Kitahara A.R., Zalameda J.N., Glaessgen E.H.

AbstractThe widespread adoption of additive manufacturing (AM) in different industries has accelerated the need for quality control of these AM parts. Some of the complex and labor-intensive challenges associated with qualification and certification of AM parts are addressed by modeling and monitoring process conditions. Quantifying melt-track process conditions remains a significant computational challenge due to the large-scale differential between melt pool and part volumes. This work explores a novel point field (PF) driven AM model-based process metric (AM-PM) approach for calculating melt track resolved process conditions with maximal computational speed. A cylindrical Ti-6Al-4V test article with 16 equiangular zones having varied process parameters was built. The melt-track resolved AM-PMs were calculated and mapped to porosity existence for the 5.8-million-point PF of the test article. AM-PMs were calculated in 6.5 min, ~ 665 × faster than a similarly sized finite element calculation. This approach enables efficient prediction, assessment, and adjustment of AM builds. Graphical abstract

Molina V., Maier O., Göhlich D.

The implementation of additive manufacturing enables the re-thinking of a product architecture towards an optimized design and functional integration. This study builds upon existing function-oriented part identification methods. These approaches have been further developed towards identifying and evaluating potential product redesigns for powder bed (Laser Powder Bed Fusion), powder spray (Cold Spray), and hybrid additive manufacturing. Our method is capable of analyzing complex industrial product structures. The feasibility of the method is demonstrated for a gas turbine combustion unit.

Rudolph K., Kübler M., Noack M., Kirchner E.

In additive manufacturing, differential design is becoming increasingly important as a complementary design method to integral design. Consequently, the need for component connections increases. In preliminary investigations, electrochemical metal deposition has been shown to be promising as a joining method. In this publication, the process preparation steps are improved. Subsequently, the influence of geometry parameters on the material distribution in the joining zone is considered using specimen made of AlSi10Mg. For this purpose, characterizing features of the finished joint are identified and the effect of geometry on these features is investigated. In addition, a brief comparison of the effect of geometry on the tensile strength of a purely material bonded joint is drawn. An opposite behavior between improved tensile strength and reduction of material agglomeration is found. Finally, suggestions are given for improving the joint by modifying part design and process based on the current state of research.

Hossain M.S., Chakrabortty R.K., Elsawah S., Ryan M.J.

Modular product family architecture (PFA), in coordination with the supply chain, assists manufacturers in achieving lower costs and higher efficiency by sharing a common platform. Despite its advantages, however, the prevailing practice of PFA emphasises architectural aspects that do not focus on the interface requirements for an efficient supply chain. In particular, the individual modules and components are assumed to have equal and/or fixed connection values, thereby overlooking the impact of modularity on the supply chain architecture (SCA). Explicit considerations of alternative modular configurations can invoke changes in granularity to reduce supply chain costs. Furthermore, the general approach of SCA is predominately focused on cost without emphasising commonality, reducing the benefit of modularity. The major challenge is, therefore, to determine the optimal granularity of modules under a coherent framework of product family modularity and supply chain modularity, which are often widely different. To resolve the problem, a bi-level programming (BLP) model is proposed in which the integrated effects of commonality and cost of supply chain modularity are investigated with the architectural and interface modularity (AIM) of product design. The proposed leader–follower decision structure interactively and hierarchically optimises commonality and cost to ensure product design and supply chain coherence and integrity. The experimental results for refrigerator PFA and its supply chain reveal that the proposed integrated modularisation model saves 11.54% and 5.95% SCA cost compared with cost-based and commonality-based models. In algorithmic comparisons, the proposed nested bi-level particle swarm optimisation (NBL-PSO) shows an enhanced performance for various problem instances with lower standard deviation (design cost: 3.3% and SCA cost: 6.4%) compared with the genetic algorithm.

Sanowar Hossain M., Chakrabortty R.K., El Sawah S., Ryan M.J.

Incorporating interface modularity into the traditional structural–functional modular-based product family architecture (PFA) is of paramount importance for efficient assembly configuration. The structural–functional modularity for PFA only ensures technical system modularity (TSM) with the increasing complexity of assembly and leads to a high redesign cost. In particular, the individual modules and components are assumed to have equal and/or fixed connection values, thereby overlooking the impact of modularity on the assembly configuration. The major challenge for integrating assemblability into a PFA is determining the optimal granularity of modules under the coherent framework of TSM and interface modularity which is often widely different. Responding to the challenge, a decision hierarchy is presented to describe the concurrent decisions of the PFA and assembly configuration through a multi-objective bi-level leader–follower joint optimization (LFJO). The main objective is to maximize profit by ensuring modules with higher commonality and lower interface complexity, which facilitates the design and assembly processes. Consistent with the bi-level optimization, a multi-objective nested bi-level genetic algorithm (M-NBGA) is developed to solve the bi-level LFJO problem efficiently. Numerical examples (i) demonstrate the applicability of the proposed model and algorithm, (ii) manifest the benefit of considering the level of interactions to deal with the product architecture, (iii) validate the contribution of interface modularity in reducing assembly complexity, and (iv) reveal the effect of modular granularity on design and assembly cost.