Design and Implementation of New Coplanar FA Circuits without NOT Gate and Based on Quantum-Dot Cellular Automata Technology

The miniaturization of electronic devices and the inefficiency of CMOS technology due to the development of integrated circuits and its lack of responsiveness at the nanoscale have led to the acquisition of nanoscale technologies. Among these technologies, quantum-dot cellular automata (QCA) is considered one of the possible replacements for CMOS technology because of its extraordinary advantages, such as higher speed, smaller area, and ultra-low power consumption. In arithmetic and comparative circuits, XOR logic is widely used. The construction of arithmetic logic circuits using AND, OR, and NOT logic gates has a higher design complexity. However, XOR gate design has a lower design complexity. Hence, the efficient and optimized XOR logic gate is very important. In this article, we proposed a new XOR gate based on cell-level methodology, with the expected output achieved by the influence of the cells on each other; this design method caused less delay. However, this design was implemented without the use of inverter gates and crossovers, as well as rotating cells. Using the proposed XOR gate, two new full adder (FA) circuits were designed. The simulation results indicate the advantage of the proposed designs compared with previous structures.

A method to assess design complexity of modular automatic assembly system in design phase

Purpose To find the system with minimum investment and best quality performance that is capable of producing all of the product variants, assessing the complexity of designing assembly system at the early concept stage is an essential step, which helps and instructs a designer to create a product- and system-oriented assembly solution with the least complexity. The purpose of this paper is to propose a quantifying measurement of complexity in the design of a modular automated assembly system. Design/methodology/approach The configurable assembly system is becoming a trend, which enables companies to quickly respond to changes caused by different product variants but without a large investment. One of the enabling factors is the availability of modular solutions of assembly modules that can be configured according to different technical requirements. This paper develops a methodology using fuzzy evaluation to calculate the design complexity in the design phase for a modular automatic assembly system. Fuzzy linguistic variables are used to measure the interaction among the influence factors, to deal with the uncertainty of the judgement. The proposed method investigates three matrices to present how the function-based assembly modules, design complexity factors, part attributes and product components, which are regarded as the main influence factors, complicate the construction of a modular assembly system. The design complexity is derived and quantified based on these assessments. Findings The proposed approach presents a formal quantification to evaluate the design complexity with regard to a modular assembly system from beginning, which can be identified and used as criteria to indicate the quality of performance and investment cost in advance. A mathematical model based on the fuzzy logic is established to provide both theoretical and practical guidance for the paper. To validate the predictive model, the statistic relationships between the assessed system design complexity, real assembly defect rate and investment cost are estimated based on regression analysis. The application of the presented methodology is demonstrated with regard to a traditional rear drive unit in the automotive industry. Originality/value This paper presents a developed method, which addresses the measures of complexity found in the design of a modular assembly system. It would help to run the design process with better resource allocation and cost estimation in a quantitative approach.

Using the REA Data Model in Order to Reduce Design Complexity in an Inventory Management Relational Database, and the Need for a Relational Database Complexity Metric.

With the extensive use of relational databases in the business environment there is a need to reduce database complexity in order to avoid data inconsistency and redundancy, which can provide a company with unreliable and/or meaningless data and information. The use of the REA Data Model in database design can significantly help with this problem. The model can eliminate the need for unnecessary data artifacts which should only be generated by the system when needed. This paper also addresses the need for a Relational Database Complexity Metric. A simple and easy to understand metric is presented.

An Approach to Measuring Ship Design Complexity

Understanding different aspects of complexity and measuring them properly are important steps of handling ship design complexity effectively. The main objective of this article is to develop a practical and comprehensive method to measure ship design complexity. In engineering design, complexity is measured today by different indexes and methods. This paper initially explores the applicability of such measures in a ship design context supported by a review of different relevant user-cases. However, it is acknowledged that most of these measurement methods focus on product-related complexity aspects and rarely address or quantify complexities generated by the design process, the organisation of the firm, or the market situation. Therefore, this paper introduces a new and comprehensive model to measure ship design complexity including all these aspects. The model quantifies ship design complexity by means of the following nine different descriptive factors: directional, spatial, decision-making, structural, behavioral, contextual, perceptual, temporal, and technological complexity.

Ship design complexity, sources, drivers, and factors: A literature review

Handling complexity in conceptual ship design processes requires a thorough understanding of complexity aspects in general. More than 100 scientific papers on the subject published since 1962 are, therefore, reviewed and discussed in this paper. The paper expands the understanding of complexity theory by reviewing the literature in the engineering domain. Different definitions of complexity, characteristics of complex systems, aspects of complexity in design, complexity sources, and its drivers are explored and discussed in detail. Furthermore, the findings are arranged into relevant complexity factors in ship design. Related complexity factors in ship design, are also discussed by use of examples from everyday ship design practices. This study is a theoretical elaboration to shed light on the current practice and future research direction in handling complexity in conceptual ship design processes to improve competitiveness.

Influence of Ship Design Complexity on Ship Design Competitiveness

Complexity is discussed in design literature mainly through its negative and in some cases positive consequences. This article critically reviews and elaborates the effects of complexity on competitiveness in ship design, its directionality, and magnitude. The article introduces a model for the measurement of ship design complexity and ship design competitiveness based on predefined factors. Archival data of 100 ship design projects from eight different Norwegian designers are used as case study. Multivariate data analysis techniques are employed to study the research model. The results show a significant correlation between complexity and competitiveness in ship design, where the magnitude and directionality of influence vary among different complexity factors. Our findings provide a basis for enhancing complexity management in ship design. Introduction Continual technology improvements and market volatility with its associated uncertainties have a significant impact on and partly change ship design customers’ expectations. To be successful in such a market, not only does it require the development of competitive products but also the accompanying work processes and the organization or firm framing the development of the vessel solution are involved. Ulstein and Brett (2015) define ship design competitiveness in terms of doing the right thing (effectiveness), doing the right thing right (efficiency), and with the right resources (efficacy) to cover product, process, and firm aspects of competitiveness. To improve their success, ship design companies typically tend to focus on the introduction of new technologies, and, in some cases, extra functional capabilities, which have led to large and complex vessels over the years. To a lesser extent, ship designers have put emphasis on the overall needs of customers. Securing a higher overall performance yield of the ship design solution than peer vessels out in the market is not a common practice among ship designers; they rather focus on a typical and traditional subset of performances. The implications and the consequences of such strategies in ship design have led to a growing need for a new set of design tools and project-making skills, a more extensive design process with different disciplines involved, and many iterations in the design development process.

Machine Learning for Electronic Design Automation: A Survey

With the down-scaling of CMOS technology, the design complexity of very large-scale integrated is increasing. Although the application of machine learning (ML) techniques in electronic design automation (EDA) can trace its history back to the 1990s, the recent breakthrough of ML and the increasing complexity of EDA tasks have aroused more interest in incorporating ML to solve EDA tasks. In this article, we present a comprehensive review of existing ML for EDA studies, organized following the EDA hierarchy.