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The purpose of this paper is to propose a method to aid design practitioners and students towards the design of additive manufactured products or parts produced using laser sintering (LS).

A design feature taxonomy was first developed as a guide for the development of a computer‐based design support tool. It comprised four taxons based on the reasons for utilising additive manufacturing (AM). These were user fit requirement, improved product functionality, parts consolidation and improvement of aesthetics or form. Each of the requirements was further expanded into 13 sub‐categories that contained examples of various design features that was then represented in the form of an MS Access database.

Results from user trials of the database provide evidence to show the potential of the database, as it enables users to easily visualise and gather information about AM design features.

The paper describes a database, the aim of which is to serve as a collective source of information for design features produced by AM and as a method to aid the conceptual design process of AM parts or products.

In this paper the authors aim to review the state-of-the-art literature on online review systems and their impacts on consumer behavior and retailers' performance with the aim of identifying research gaps related to different design features of review systems and developing future research agenda.

The authors conducted a systematic review based on PRISMA 2020 protocol, focusing on studies published in the domains of retailing and marketing. This procedure resulted in 48 selected papers investigating the design features of retailer online review systems.

The authors identify eight design features that are controllable by retailers in an online review system. The design features have been researched independently in previous literature, with some features receiving more attention. Most selected studies focus on the design features adapted metrics and review presentations, while other features are generally neglected (e.g. rating dimensions). Previous literature argues that design features affect consumer behaviors and retailers' performance. However, the interactions among the features are still neglected in the literature, creating a relevant gap for future research.

This paper distinguishes between different types of retailer online review systems based on how they are implemented. The authors summarize the state-of-the-art of relevant literature on design features of online review systems and their effects on consumer- and retailer-related outcome variables. This systematic literature review distinguishes between online reviews provided on websites controlled by retailers (internal systems) and third-party websites (external systems).

The purpose of this paper is to determine the suitability of adopting hybridized multicriteria decision-making models as a decision tool in engineering design. This decision tool will assist design engineers and manufacturers to determine a robust design concept before simulation and manufacturing while all the design features and sub features would have been identified during the decision-making process.

Fuzzy analytical hierarchy process (FAHP) and fuzzy technique for order preference by similarity to ideal solution (FTOPSIS) are hybridized and applied to obtain optimal design of a reconfigurable assembly fixture (RAF) from a set of alternative design concepts. Design features and sub features associated with the RAF are identified and compared using fuzzified pairwise comparison matrices to obtain weights of their relative importance in the optimal design. The FAHP obtained the fuzzy synthetic extent (FSE) values of the design features and sub features. The FSE values are used as weights of the design features and sub features in generating the decision matrix. FTOPSIS and FTOPSIS based on left and right scores were adopted to predict effects of the weights. Results were obtained for normalized and unnormalized weights of the design features and its effects on the relative closeness coefficients of the design alternatives.

The improved performance of the FTOPSIS based on left and right scores is due to the involvement of the left and right scores of weights of the design features in the computation of distances from positive and negative ideal solutions. Embedding the weights of the design features in the normalized decision matrix before estimating the distances of the design concepts from ideal solutions reduces the dependency of the closeness coefficients on the weights of the design features. This also decreases the difference in the final values of the design concepts. In essence, the weights of the design features have an impact in the closeness coefficient. There is reduction in the closeness coefficients of the design concepts due to normalization of the weights of the design features. However, normalizing the weights of the design features did not affect the variations in the final values of the design concept. As the final value of the design concepts can be influenced by the normalized weights of the design features, it can be implied that normalization of weights of the sub features will also affect the decision matrix. The study has been able to proof that hybridizing FAHP and FTOPSIS can produce effective results for decisions on optimal design by the application of FTOPSIS based on left and right scores rather than the general FTOPSIS.

This research develops a hybridized multicriteria decision-making model for decision-making in engineering design. It presents a detailed extension of hybridized FAHP and FTOPSIS based on left and right scores as a useful tool for considering the relative importance of design features and sub features in optimal design selection.

Although brands have developed mobile applications (apps) to offer consumers new experiences, low app usage numbers indicate the need to develop a systematic, practical evaluation framework for branded app design that specifies concrete design features.

An expert review provides an overview of the design of current branded apps. On the basis of an extensive literature review, this article classifies state-of-the-art design features for branded apps according to a proposed evaluation framework that includes human–computer interaction (HCI)–related and marketing-related evaluation criteria. In an application of these evaluation criteria, the authors evaluate 73 branded apps issued by 11 top fast-moving consumer goods (FMCG) brands.

The expert review identifies strengths and weaknesses that are common to the design of current branded apps. These findings inform the set of design recommendations that this article offers, which includes 14 features common to all types of apps and 9 features specific to particular types of apps.

This research offers practical implications for app designers, who need to address design dimensions contained in the proposed framework including the HCI-related (mobile, social and user experience design features) and marketing-related (branding and customer relationship management design features) to create effective branded apps.

Design elements identified in prior literature remain abstract and do not prescribe a systematic or pragmatic approach to using them in practice. This study takes a multidisciplinary perspective (HCI, marketing and design science) to establish a practical evaluation framework for branded app designs.

This paper aims to study the appearance of drills from one brand by using currently available design tools. It aims to find and discuss the relationship between appearance innovation and maintaining key design features.

The innovation process is studied on drills of a Czech power tool maker and a previously created concept of a new drill. First, the authors explore the similarities between the designed concept and previous models of the brand by calculating the degree of similarity of given shape features. Second, they capture the drills simple shape grammar and strive to generate a sketch of the concept.

Results show the use of several similar shape features from previous models in the innovated design. Shape grammar can create a principally similar concept, but some innovations cannot be achieved this way. A description of appearance innovation within brand identity in terms of shape grammar is given.

The research is limited mainly to a small group of previous products that can be analyzed. It is done only for one particular brand identity. When used with the shape grammars, design generation is limited.

Better understanding of the innovative process aids designers in working with designs for brand identity and may serve to shape grammar enhancement.

The paper describes what happens during the innovation of product appearance and implicates enhancement and meaning of design analysis done by shape grammars and exploring similarities.

This paper introduces a schema for the product assembly feature data in an object-oriented and module-based format using Unified Modeling Language (UML). To link production with product design, it is essential to determine at an early stage which entities of product design and development are involved and used at the automated assembly planning and operations. To this end, it is absolutely reasonable to assign meaningful attributes to the parts’ design entities (assembly features) in a systematic and structured way. As such, this approach empowers processes such as motion planning and sequence planning in assembly design.

The assembly feature data requirements are studied and definitions are analyzed and redefined. Using object-oriented techniques, the assembly feature data structure and relationships are modeled based on the identified requirements as five UML packages (Part, three-dimensional (3D) models, Mating, Joint and Handling). All geometric and non-geometric design data entities endorsed with assembly design perspective are extracted or assigned from 3D models and realized through the featured entity interface class. The featured entities are then associated (used) with the mating, handling and joints features. The AssemblyFeature interface is realized through mating, handling and joint packages related to the assembly and part classes. Each package contains all relevant classes which further classify the important attributes of the main class.

This paper sets out to provide an explanatory approach using object-oriented techniques to model the schema of assembly features association and artifacts at the product design level, all of which are essential in several subsequent and parallel steps of the assembly planning process, as well as assembly feature entity assignments in design improvement cycle.

The practical implication based on the identified advantages can be classified in three main features: module-based design, comprehensive classification, integration. These features help the automation and solution development processes based on the proposed models much easier and systematic.

The proposed schema’s comprehensiveness and reliability are verified through comparisons with other works and the advantages are discussed in detail.

This paper aims to present a hybrid machine learning algorithm for additive manufacturing (AM) design feature recommendation during the conceptual design phase.

In the proposed hybrid machine learning algorithm, hierarchical clustering is performed on coded AM design features and target components, resulting in a dendrogram. Existing industrial application examples are used to train a supervised classifier that determines the final sub-cluster within the dendrogram containing the recommended AM design features.

Through a case study of designing additive manufactured R/C car components, the proposed hybrid machine learning method was proven useful in providing feasible conceptual design solutions for inexperienced designers by recommending appropriate AM design features.

The proposed method helps inexperienced designers who are newly exposed to AM capabilities explore and utilize AM design knowledge computationally.

This paper aims to apply the augmented reality (AR) technology to assembly design in the early design stage. A proof‐of‐concept system with AR interface is developed.

Through AR interface, designers can design the assembly on the real assembly platform. The system helps users to design the assembly features to provide proper part‐part constraints in the early design stage. The virtual assembly features are rendered on the real assembly platform using AR registration techniques. The new evaluated assembly parts can be generated in the AR interface and assembled to assembly platform through assembly features. The model‐based collision detection technique is implemented for assembly constraint evaluation.

With AR interface, it would be possible to combine some of the benefits of both physical and virtual prototyping (VP). The AR environment can save a lot of computation resource compared to a totally virtual environment. Working on real assembly platform, designers have more realistic feel and the ability to design an assembly in a more intuitive way.

More interaction tools need to be developed to support the complex assembly design efficiently.

The presented system encourages designers to consider the assembly issues in the early design stage. The primitive 3D models of assembly parts with proper part‐part constraints are generated using the system before doing detailed geometry design.

A new markerless registration approach for AR system is presented. This generic approach can be also used for other AR applications.

Currently, the design, technological features of voices, and their analysis of various applications are being simulated with the requirement to communicate at a greater distance or more discreetly. The purpose of this study is to explore how voices and their analyses are used in modern literature to generate a variety of solutions, of which only a few successful models exist.

The mel-frequency cepstral coefficient (MFCC), average magnitude difference function, cepstrum analysis and other voice characteristics are effectively modeled and implemented using mathematical modeling with variable weights parametric for each algorithm, which can be used with or without noises. Improvising the design characteristics and their weights with different supervised algorithms that regulate the design model simulation.

Different data models have been influenced by the parametric range and solution analysis in different space parameters, such as frequency or time model, with features such as without, with and after noise reduction. The frequency response of the current design can be analyzed through the Windowing techniques.

A new model and its implementation scenario with pervasive computational algorithms’ (PCA) (such as the hybrid PCA with AdaBoost (HPCA), PCA with bag of features and improved PCA with bag of features) relating the different features such as MFCC, power spectrum, pitch, Window techniques, etc. are calculated using the HPCA. The features are accumulated on the matrix formulations and govern the design feature comparison and its feature classification for improved performance parameters, as mentioned in the results.

The objective is to develop a flexible robot assembly system capable of economically switching between a wide range of product assemblies. Towards this goal, this paper introduces grasping as a principle issue in designing for flexibility in a robot system. The task, sensing, and certainty about actions are the primary factors in grasp decisions and not where to grasp the part. Identifying finger features, which satisfy a broad range of tasks reduces the likelihood of re‐tooling, and improves certainty about part location and relative orientation. Aided by the ability to address a broad range of tasks, design rules are established which assimilate grasps to part design.