Showing papers on "Product design specification published in 2021"

Engineering Design Methods: Strategies for Product Design

Abstract: About the Author. Acknowledgements. Introduction. Part One: Understanding Design. 1. The Nature of Design. Design Activities. Design Problems. Problem Structures. 2. Design Ability. What Designers Say. How Designers Think. Learning to Design. 3. The Design Process. Descriptive Models. Prescriptive Models. An Integrative Model. Part Two: Doing Design. 4. New Design Procedures. Systematic Procedures. Design Methods. Creative Methods. Rational Methods. 5. Identifying Opportunities. The User Scenarios Method. 6. Clarifying Objectives. The Objectives Tree Method. 7. Establishing Functions. The Function Analysis Method. 8. Setting Requirements. The Performance Specification Method. 9. Determining Characteristics. The Quality Function Deployment Method. 10. Generating Alternatives. The Morphological Chart Method. 11. Evaluating Alternatives. The Weighted Objectives Method. 12. Improving Details. The Value Engineering Method. Part Three: Managing Design. 13. Design Strategies. What is a Design Strategy? Frameworks for Action. Strategy Control. Setting Strategies and Choosing Tactics. 14. Product Development. Product Design. Product Planning. Product Innovation. References. Index.

Knowledge-Empowered Multitask Learning to Address the Semantic Gap Between Customer Needs and Design Specifications

Abstract: Smart manufacturing attempts to build a collaborative and integrated platform to enable flexibility in product design and manufacturing processes so as to better address customer needs. This makes a smooth information flow a prerequisite for smart manufacturing. However, firms usually struggle with a lack of consistency and coherence in communication and information exchange in design and manufacturing practices, a phenomenon called “semantic gap.” This article presents a multitask learning framework to close the semantic gap between customers and designers/engineers to facilitate efficient product codevelopment. We elicited domain knowledge from a product review text corpus and integrated the knowledge into a bidirectional long short-term memory-based multitask learning network. Transfer learning was then applied to adapt the network so it could bridge the semantic gap between customer needs and product specifications. Experiment results indicate that the proposed method unites customer needs and product specifications in smart manufacturing by effectively mapping across these domains.

A Methodology for Emulsion Design Based on Emulsion Science and Expert Knowledge. Part 1: Conceptual Approach

Abstract: Formulated emulsions have a high commercial value due to their multiple applications in several product sectors such as cosmetics, nutrition, medicine, and household products, among others. Their design is not a simple task because emulsions are complex systems in which components, structures, phenomena, and processes are highly interrelated. Thus, any decision must be made with its multiple effects on the final product’s properties in mind. Emulsion design is even more challenging at early design stages when information is scarce and critical design decisions are made. In view of the above, this study proposes a decision-making methodology for emulsion formulation applicable to early product design/screening/exploratory stages. It enables product designers to understand the product as a whole system and select a set of complementary solution strategies applicable to their specific emulsion formulation problem. The methodology presented in detail in this article comprises three steps and uses two databases, which were proposed based on emulsion science principles and connected thanks to a database of expert knowledge. In the first step, product specifications are classified according to a list of 21 general subproblems in emulsion formulation, which are related to physicochemical phenomena or properties that are to be promoted or limited in the product. In the second step, subproblems are connected to a list of 30 general solution strategies, which are solution paths related to the emulsion’s nature or structure but not initially directly related to a specific compound or process technology. In the third step, solution strategies are connected to compound types and processing conditions using a second database with the aim of creating potential design concepts.

Nanotechnology in Solar Still: Conceptual Design

Abstract: Nanomaterials have many applications Improving the heat transfer characteristics of the substance is one of the most important applications of nanomaterials A solar still is a device that desalinates saline or impure water using solar energy In the present work, a conceptual design approach is used to design a solar still utilizing nanomaterials The customer requirements are collected based on an online survey Based on these requirements, the product specifications are specified The customers' voice is heard through quality function deployment, and several alternatives are proposed in the morphological chart By comparing the alternatives, the best one is chosen using the decision matrix

E-commerce Product Recommendation Based on Product Specification and Similarity

Abstract: Recommender systems play the role of leading users to customized suggestions in the broad universe of available possibilities. While producers use it for cross-selling, which suggests additional products or services to customers, consumers use recommender systems to seek items that match their interests and preferences. By establishing a value-added relationship between the system and the customer, recommender systems boost loyalty. In present e-commerce systems, user pattern search, item, and historical analysis is a substantial component of a recommendation system. A better recommendation system based on product specifications and product similarity measures rather than historical data could lead to a progressive change in e-commerce recommendation technologies. This paper proposes a model that uses product specifications and various similarity measures to compute the user recommendations. The model considers product description and specifications to calculate a similarity measure and then uses these similarity values to form clusters of products. Based on the generated cluster of products, relevant products are recommended to the user. The paper presents method analysis of the various measures and matrices using a sample data set. It also compares the results of our model with the traditionally followed model. The proposed methodology promises to build a user-friendly recommendation system.

Application of Design for Sustainability to Develop Smartphone Holder Using Roselle Fiber-Reinforced Polymer Composites

Abstract: The product development process of roselle fiber-reinforced polymer composite smartphone holder by using the design for sustainability approach is presented in this chapter. Concept development of the environmental-friendly smartphone holder product was carried out using concept generation and concept evaluation techniques. The roselle composite smartphone holder development process involved in this work included market analysis, product design specification document generation, plaque conceptual design creation, and detailed design of the finished product. The roselle fiber composite smartphone holder was fabricated using hand layup process. In the end, the final product accomplished easy manufacturing technique, lightweight, low cost, and acceptable equilibrium between functionality and aesthetic.

Developing a Product Knowledge Graph of Consumer Electronics to Manage Sustainable Product Information

Abstract: Transformational computing paradigms, such as artificial intelligence, home automation, and the Internet of Things, are being rapidly applied to consumer electronics products, thus aiding in the development of integrated and innovative features. Hence, ubiquitous computing and electronic devices are increasingly becoming essential to everyday life. In this context, a wide gulf often exists between the capabilities and technical features of consumer electronic devices and the consumers’ understanding of such devices and ability to operate them correctly and effectively. This study proposes a machine-readable knowledge model representing technical terms in product specifications along with a product knowledge graph to discover semantic relationships among various products. Formal concept analysis is applied to conceptually analyze the specification terms of heterogeneous electronic products and design a hierarchical knowledge structure of extracted concepts, to elaborate the proposed knowledge model.

Fashion Classification and Object Detection Using CNN

Abstract: Shopkeepers once were the best choice for product details and were also guiding consumers to navigate the buying process. But technology has turned this scenario in reverse. With every minute of change in technology, information right from product specification to product analysis is all available online. With the help of practical policy of return on offer for E-commerce sites offering flexible return policies, it has become imperative for sellers to provide premium quality and customer service well. In this paper, we have demonstrated the effectiveness of computer vision for object detection methods. We have put forth the best method to get the dress type in the picture and give the exact name of that particular dress from the different journal papers. Here, we have used the VGG16 layer ConvNet architecture using multiple layers to get more effective results. In the proposed methodology, we came up with the few basic steps that are data preprocessing (Yamaguchi et al in 2012 IEEE conference on computer vision and pattern recognition, pp 3570–357, 2012 [1]), training (Lao and Jagadeesh in Convolutional neural networks for fashion classification and object detection, 2015 [2]), compilation, validation and model performance. The proposed method is experimentally tested, verified and found acceptable by achieving accuracy of 95%.

Alaska: A Flexible Benchmark for Data Integration Tasks.

Abstract: Data integration is a long-standing interest of the data management community and has many disparate applications, including business, science and government. We have recently witnessed impressive results in specific data integration tasks, such as Entity Resolution, thanks to the increasing availability of benchmarks. A limitation of such benchmarks is that they typically come with their own task definition and it can be difficult to leverage them for complex integration pipelines. As a result, evaluating end-to-end pipelines for the entire data integration process is still an elusive goal. In this work, we present Alaska, the first benchmark based on real-world dataset to support seamlessly multiple tasks (and their variants) of the data integration pipeline. The dataset consists of ~70k heterogeneous product specifications from 71 e-commerce websites with thousands of different product attributes. Our benchmark comes with profiling meta-data, a set of pre-defined use cases with diverse characteristics, and an extensive manually curated ground truth. We demonstrate the flexibility of our benchmark by focusing on several variants of two crucial data integration tasks, Schema Matching and Entity Resolution. Our experiments show that our benchmark enables the evaluation of a variety of methods that previously were difficult to compare, and can foster the design of more holistic data integration solutions.

Prototypes for automating product system model assembly.

Abstract: The flexibility of life cycle inventory (LCI) background data selection is increasing with the increasing availability of data, but this comes along with the challenge of using the background data with primary life cycle inventory data. To relieve the burden on the practitioner to create the linkages and reduce bias, this study aimed at applying automation to create foreground LCI from primary data and link it to background data to construct product system models (PSM). Three experienced LCA software developers were commissioned to independently develop software prototypes to address the problem of how to generate an operable PSM from a complex product specification. The participants were given a confidential product specification in the form of a Bill of Materials (BOM) and were asked to develop and test prototype software under a limited time period that converted the BOM into a foreground model and linked it with one or more a background datasets, along with a list of other functional requirements. The resulting prototypes were compared and tested with additional product specifications. Each developer took a distinct approach to the problem. One approach used semantic similarity relations to identify best-fit background datasets. Another approach focused on producing a flexible description of the model structure that removed redundancy and permitted aggregation. Another approach provided an interactive web application for matching product components to standardized product classification systems to facilitate characterization and linking. Four distinct steps were identified in the broader problem of automating PSM construction: creating a foreground model from product data, determining the quantitative properties of foreground model flows, linking flows to background datasets, and expressing the linked model in a format that could be used by existing LCA software. The three prototypes are complementary in that they address different steps and demonstrate alternative approaches. Manual work was still required in each case, especially in the descriptions of the product flows that must be provided by background datasets. The study demonstrates the utility of a distributed, comparative software development, as applied to the problem of LCA software. The results demonstrate that the problem of automated PSM construction is tractable. The prototypes created advance the state of the art for LCA software.

Proposing a specification structure for complex products in model-based systems engineering (mbse)

Abstract: This research work presents a methodological support for the specification of complex products. This is achieved by developing a specification structure in a MBSE environment. The new method draws on success factors of complex product specification, principles of MBSE and the explanatory model of PGE – Product Generation Engineering. For evaluation, the method is applied within a student development project. A high applicability and the realization of novel synergies for coping with continuously increasing product complexity is demonstrated.

The perspectives of clinicians on enriching patient experiences in a clinical context: a qualitative study

Abstract: Understanding the viewpoint of clinicians in a healthcare setting is a vital task to comprehend the success of patients undergoing physical rehabilitation. Addressing user experience is an essential activity which designers undertake when formulating product specifications at the early stages of product design. The involvement of clinicians during the product use-phase influences the progress and achievements attained by the patients throughout their rehabilitation journey. Several clinicians (n=16) were asked to participate in a qualitative study to evaluate the performance of different personae in activities of daily living. The experiences of patients who use rehabilitation products as part of their therapy session at the clinic were evaluated. Based on this evaluation, a set of clinician requirements were formulated to reflect the overall experience when using rehabilitation products. Understanding these requirements brought about several implications to be considered during the design cycle. Through these considerations and by adopting a user-centred design approach, designers are in a better position to design innovative products targeted at providing a high-quality user experience which increases customer satisfaction.

An Integrated Approach for Eco-Design and Its Application in LED Lighting Product Development

Abstract: Lighting products are essential for our modern life nowadays, but they also produce high negative impacts on the environment. Although there are tools and methods available for reducing the environmental impact of lighting products, it is a challenging task to integrate them throughout the product development process. To overcome the challenge, this research developed an approach to integrate tools/methods relevant for the eco-design through product development process to reduce the environmental impact of lighting products. Six types of methods, such module design, and 30 tools, such as lifecycle assessment software packages, are considered in the integrated approach. The product specification with eco-constrains is established for implementation at each design stage to ensure the product eco-features. The approach was applied in the development of an LED table lamp which was then assessed in comparison with a benchmark LED lamp regarding environmental lifecycle impact and lighting performance. The comparative assessment results indicate that the LED lamp developed with this approach is much better than the benchmark lamp.

Cost Projections for the Product Life Cycle at the Early Stages of Product Development

Abstract: The paper is concerned with predicting the total cost of a new product and searching for cost reduction at the early stages of product development. The costs of a new product development project, product promotion, production and after-sales service are predicted using parametric models. The identified relationships are also used to searching for possibilities to reduce the cost of faulty products and after-sales service through increasing prototype tests. As a result, the trade-off between the cost of a product development project and costs of production and after-sales service are sought. Company resources and product specification are formulated in terms of variables and constraints that constitute the systems approach for a problem related to cost optimization. This problem is described in the form of a constraint satisfaction problem and implemented using constraint programming techniques. An example shows the applicability of the proposed approach in the context of searching for the desirable level of the cost related to prototype tests, faulty products and after-sales service. This study develops previous research in the context of adding the cost of after-sales service to a model of total costs of a new product. Moreover, the proposed method of predicting cost has been developed towards using the similarity value to data selection.

The culture of product development in student organisations

Abstract: Product development in a multidisciplinary student organisation brings many challenges; varying experience, adaptation and involvement of members. This article will discuss how a multidisciplinary student project maintains a learning culture for product development and project management. The identified factors for a learning culture; 1) define product specifications, 2) involve alumnis, 3) facilitate an open minded culture for failure and learning and 4) collect experience and adapt an agile framework suitable for the project. These are factors that should be an implemented part to increase the chances of maintaining a learning culture. Align Racing UiA, the case of this study, is a student organisation with over 60 engaged students in multi-disciplinary challenges. The common team goal is to produce one race car a year and compete in Formula Student. The rules for the technical side of the project are substantial, resulting in concrete boundaries to realize the project. However, every piece of the car is designed, produced and assembled by the members. Looking at the first year of Align Racing UiA, the initial project management was not optimal for a student project of this scale. Consequently, it was realized that a strong emphasis on project management, agile development method and communication would be key to a more efficient product development and project management.

Consumer Sentiment Analysis to E-Commerce in the Covid-19 Pandemic Era

Abstract: This study aims to identify e-commerce problems during the Covid-19 pandemic as a basis for providing recommendations for improving e-commerce services. The methods used in this research are Naive Bayes Classifier (NBC), Text Association, and Focus Group Discussion (FGD). The NBC method is used to classify consumer sentiment, while the Text Association is to find the relationship between words. The data source used is consumer reviews submitted on Twitter for the period January-April 2021. The FGD method is used to classify the results of the Text Association into service marketing mix elements, identify root causes using Fishbone Diagrams and develop recommendations for improvement. The respondents involved in the FGD were e-commerce experts representing practitioners and academics. The result of the improvement recommendation is: educating sellers always to provide accurate product specification information and implementing quality control; increasing mutually beneficial cooperation with logistics service providers, especially concerning service commitments and cutting shipping costs; improve information disclosure of promotional events; improve the refund procedure; optimization of multichannel e-commerce software; increase accuracy in the process of selecting and verifying prospective seller data; improve transaction process monitoring; optimizing the application of a reward and punishment system based on consumer reviews.

Influence of specifications according to the system of geometrical product specifications (gps) on scrap in technical products

Abstract: The success of a company is directly linked to its economic objectives. One of the elementary objectives is to maximize profit by reducing the company's own costs in order to increase competitiveness in the market. State of the art is the function-oriented and unambiguous technical specification through the application of Geometrical Product Specifications (GPS). Linking costs related to the GPS system is currently only possible to a limited extent. This contribution presents an approach to quantify costs based on statistical tolerance analysis. The application is intended to determine the impact of a GPS-compliant specification in direct comparison to a non-compliant technical drawing by analyzing scrap rates. In this way, an assessment of the changes associated with the consistent application of the GPS system should be achieved. The results of the study show that a comparison is only possible to a certain degree due to the different characteristics. Based on this finding, an extended evaluation methodology is described.

Conceptual design of antifungal and antibacterial herbal ear hygiene product

Abstract: Maintaining good ear hygiene is important, yet currently available ear cleaning products such as cotton buds and ear scoop might lead to internal ear injury when improperly used. This study examines the market competitiveness of a conceptual ear hygiene product based on analyzing consumer needs. This new ear hygiene product is expected to be able to clean the ear properly without exposing users to unnecessary risks, satisfy consumer needs, as well as giving added value in the form of antimicrobial properties. Consumer needs identification and reception toward the product concept were determined through online surveys to 218 respondents. Forty-eight different potential user needs were collected from survey results, which were then transformed into product specifications using the appropriate metrics. A feasibility matrix was made to compare 155 different concepts generated from mind-mapping and brainstorming processes, which results in 13 final product concepts. Further screening stages and benchmarking were applied to select the final product concept. The final concept is a topical, herbal ear hygiene product with antibacterial, antifungal, and earwax solubilization properties with micelle-based solvent in spray form. The active compound of this product is the essential oil of clove oil, also known as eugenol. The testing of the final product concept pointed towards the positive for consumer acceptance.

Technologies for using machine learning to determine product certification eligibility

Abstract: Systems and methods for using machine learning to assess eligibility for product certification are disclosed. According to certain aspects, a server computer may train a set of machine learning models using a set of training data, where the set of machine learning models may be specific to products and certifications for the products. The server computer may access product specifications associated with a set of products sought to be certified, and may analyze the product specifications using the an appropriate machine learning model(s), the output of which may indicate whether the set of products is eligible for certification, the set of products is ineligible for certification, or the product specifications need further review.

Online Shopping Decisions Enhancement with Fuzzy Expert System

Abstract: Purpose Nowadays, due to the rapid development of the Internet and the rapid growth of web pages, many electronic websites are using product recommendation systems to guide users to the products that they need. Such systems usually provide a list of suggested items that the user may prefer. These systems are provided as a support tool to help users obtain information that best meets their needs. These systems can actually improve user decisions, resulting in increased sales and mutual customer satisfaction. The purpose of the paper is to improve user decisions in online shopping using fuzzy expert system. Methodology: The statistical population of this study consists of 30 experts in the field of e-commerce who were selected by combining two methods of deliberate sampling and snowball sampling. To analyze the status of improvement of users' decisions, a fuzzy expert system was created using input variables business reputation status, environmental factors status in e-commerce, online store features; product specifications; user/customer characteristics. Findings: The final results showed that there is no significant difference between the results of the created expert system and the mean of expert opinions. Originality/Value: In this paper, a conceptual Model to improve user decisions in online shopping using a fuzzy expert system is designed.