1,638 research outputs found

    Improving product design phase for engineer to order (ETO) product with knowledge base engineering (KBE)

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    In industry currently Computer Aided Design (CAD) is an important tool for the modification, analysis, or optimization of the 3D virtual environment that replicates the physical product. CAD software is an efficient and reliable tool. However, as globalization increases customer demands, this process needs to be faster and more efficient to accommodate changing product design situations, especially for Engineer-to- Order (ETO) products. ^ The traditional method of product design process is to operate CAD software without argumentation. Design engineers create CAD prototypes and drawings based on available knowledge and information which comes from engineering experts, company standards, industrial practices as well as other sources. Research has shown that 80% of knowledge is not captured in the system. It can be time consuming for the design engineer to provide an accurate and consistent virtual product. Researchers have found that the traditional method is unreliable, inaccurate and inefficient. There is room for improvement in the product design situation for ETO products. There is a need to develop a design method that is faster and reduces costs. ^ Knowledge Base Engineering (KBE) is an alternative system that is built to capture and reuse knowledge. KBE technology is well known for reducing lead-time and design errors using automation. Through integrating KBE technology with CAD software, design engineers create virtual product configurations by applying a scripting language to the CAD model. It requires time and effort invested in a different way than traditional design method, which may cost more to develop. However it is more efficient and accurate when producing multiple configurations. ^ This research experiment is to define a better design method for the ETO product situation by comparing the traditional design method with the KBE/CAD integration method. The research question is Is the Knowledge-Based Engineering (KBE) and Computer Aided Design (CAD) integration design approach more efficient for the reduction of lead time and design error than the traditional method for Engineering-to- Order (ETO) product situations

    Stage Configuration for Capital Goods:Supporting Order Capturing in Mass Customization

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    IoT-enabled planning, control, and execution in ETO manufacturing: dynamics, requirements, and system architecture: a case study of Brunvoll AS

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    Confidential until 18. May 202

    Configuration knowledge modeling: How to extend configuration from assemble/make to order towards engineer to order for the bidding process

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    The bidding process is one of the most important phases for system contractors. A successful bid implies defining and implementing attractive and realistic systems solutions that fulfil customer expectations. An additional challenge arises with the increase in systems diversity resulting from growing customization needs. As a result, for standard customizing offers, bidders find good quality support with configuration software for assemble/make-to-order situations. But when requirements exceed the standard offers, bidders need extended support to fulfil Engineering-to-Order requirements. In this context, this article shows how configuration knowledge models, which support configuration in assemble/make-to-order situations (AMTO), can be extended and used in engineer-to-order situations (ETO). Modeling is achieved assuming that the configuration problem is considered as a constraint satisfaction problem. Six key requirements that differentiate ETO from AMTO are identified and modeling extensions are proposed and discussed. An example illustrates all the contributions

    Space transportation systems, launch systems, and propulsion for the Space Exploration Initiative: Results from Project Outreach

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    A number of transportation and propulsion options for Mars exploration missions are analyzed. As part of Project Outreach, RAND received and evaluated 350 submissions in the launch vehicle, space transportation, and propulsion areas. After screening submissions, aggregating those that proposed identical or nearly identical concepts, and eliminating from further consideration those that violated known physical princples, we had reduced the total number of viable submissions to 213. In order to avoid comparing such disparate things as launch vehicles and electric propulsion systems, six broad technical areas were selected to categorize the submissions: space transportation systems; earth-to-orbit (ETO) launch systems; chemical propulsion; nuclear propulsion; low-thrust propulsion; and other. To provide an appropriate background for analyzing the submissions, an extensive survey was made of the various technologies relevant to the six broad areas listed above. We discuss these technologies with the intent of providing the reader with an indication of the current state of the art, as well as the advances that might be expected within the next 10 to 20 years

    Warranty prediction during product development: Developing an event generation engine in an engineer-to-order environment

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    In order for manufacturing companies to stay competitive, it is necessary to drive warranty system improvements in terms of improved product reliability, improved service delivery efficiency and properly designed warranty policies. However, traditional methods for assessing warranty performance are not always sufficient to alert product development teams of the impending warranty issues. Furthermore, improved assessment methods are needed to aid product development teams make decisions related to the warranty performance of the product. The focus of this research was to develop a framework to integrate statistical inference methods and data mining techniques to create a warranty event generation framework. This was done on the context of an engineer-to-order product development environment. The objectives of this work were: (1) to develop an inference model for the integration of disparate data sources; (2) to demonstrate that multiple data streams can be conditioned for input into the above inference model; (3) to develop the above model and process in light of actual data. This thesis will report on the progress and challenges that have been made toward fulfilling these objectives. The thesis closes by outlining the future research agenda for developing a warranty event generation engine that can integrate data from disparate data sources

    IoT-technological maturity model development and maturity assessment of Norwegian manufacturing companies

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    Confidential until 24. May 202

    The Second Conference on Lunar Bases and Space Activities of the 21st Century, volume 1

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    These papers comprise a peer-review selection of presentations by authors from NASA, LPI industry, and academia at the Second Conference (April 1988) on Lunar Bases and Space Activities of the 21st Century, sponsored by the NASA Office of Exploration and the Lunar Planetary Institute. These papers go into more technical depth than did those published from the first NASA-sponsored symposium on the topic, held in 1984. Session topics covered by this volume include (1) design and operation of transportation systems to, in orbit around, and on the Moon, (2) lunar base site selection, (3) design, architecture, construction, and operation of lunar bases and human habitats, and (4) lunar-based scientific research and experimentation in astronomy, exobiology, and lunar geology

    Contextual variety, Internet-of-things and the choice of tailoring over platform : mass customisation strategy in supply chain management

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    This paper considers the implications for Supply Chain Management from the development of the Internet of Things (IoT) or Internet Connected Objects (ICO). We focus on the opportunities and challenges arising from consumption data as a result of ICO and how this can be translated into a provider’s strategy of offering different varieties of products. In our model, we consider two possible strategies: tailoring strategy and platform strategy. Tailoring strategy implies that a provider produces multiple varieties of a product that meet consumers’ needs. Platform strategy depicts the provider’s actions in offering a flexible and standardised platform which enables consumers’ needs to be met by incorporating personal ICO data onto various customisable applications independently produced by other providers that could be called on in context and on demand. We derive conditions under which each of the strategies may be profitable for the provider through maximising consumers’ value. We conclude by considering the implications for SCM research and practice including an extension of postponement taxonomies to include the customer as the completer of the product
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