Discovering a Hierarchical Design Process Model Using Text Mining

The increasing design documents created in the design process provide a useful source of process-oriented design information. Hence, the need for automated design information extraction using advanced text mining techniques is increasing. However, most of the existing text mining approaches have problems in mining design information in depth, which results in low efficiency in applying the discovered information to improve the design project. With the aim of extracting process-oriented design information from design documents in depth, this paper proposes a layered text mining approach that produces a hierarchical process model which captures the process behavior at the different level of details. Our approach consists of several interrelated algorithms, namely, a content-based document clustering algorithm, a hybrid named entity recognition (NER) algorithm and a frequency-based entity relationship detection method, which have been integrated into a system architecture for extracting design information from coarse-grained views to fine-grained specifications. To evaluate the performance of the proposed algorithms, experiments were conducted on an email archive that was collected from a real-life design project. The results showed an increase in the detection accuracy for the process-oriented information detection.

Two Approaches to the Induction of Graph-Rewriting Rules for Function-Based Design Synthesis

In this paper we demonstrate and compare two complementary approaches to the automatic generation of production rules from a set of given graphs representing sample designs. The first approach generates a complete rule set from scratch by means of frequent subgraph discovery. Whereas the second approach is intended to learn additional rules that fit an existing, yet incomplete, rule set using genetic programming. Both approaches have been developed and tested in the context of an application for automated conceptual engineering design, more specifically functional decomposition. They can be considered feasible, complementary approaches to the automatic inference of graph rewriting rules for conceptual design applications.

Standardized Vocabularies for Assembly Systems Modelling and Automation Alternatives Description

The aim of this research is to support assembly lines designers in conceiving new processes with optimal automation levels selection. Several alternatives with various automation options may exist. Graphic representations and analyses of the different designs are needed. The finality is to offer a quick, exhaustive, and reliable way of modelling alternatives based on a given product design. In this sense we propose a new assembly tasks vocabulary to be combined to an existing lower layer vocabulary of elementary motions and a graphic modelling language. These developments deal with an existing automation decision approach as an extension allowing to overcome identified gaps and to ease its implementation and computerization. The proposal facilitates assembly systems alternatives generation with automation options consideration based on an initial representation. The generated alternatives are then subject to further analyses with regard to automation criteria and performance indicators considering planned production targets.

Smart Reading Aid for Detecting Problems With Reading Fluency and Comprehension

Brain signal and eye tracking technology have been intensively applied in cognitive science in order to study reading, listening and learning processes. Though promising results have been found in laboratory experiments, there are no smart reading aids that are capable to estimate difficulty during normal reading. This paper presents a new concept that aims to tackle this challenge. Based on a literature study and an experiment, we have identified several indicators for characterizing word processing difficulty by interpreting electroencelography (EEG) and electrooculography (EOG) signals. We have defined a computational model based on fuzzy set theory, which estimates the probability of word processing and comprehension difficulty during normal reading. The paper also presents a concept and functional prototype of a smart reading aid, which is used to demonstrate the feasibility of our solution. The results of our research proves that it is possible to implement a smart reading aid that is capable to detect reading difficulty in real time. We show that the most reliable indicators are related to eye movement (i.e. fixation and regression), while brain signals are less dependable sources for indicating word processing difficulty during continuous reading.

Characterization of Antifragility in Cyber Systems Using a Susceptibility Metric

Traditional engineering design practice seeks to create reliable systems that maintain a desired minimum performance when subjected to a defined set of impulses. To manage impulses, designers implement techniques to specify systems that are resilient or robust to impulses. Resilient systems perform with degraded capacity when subjected to impulses while robust systems remain unaffected by impulses. In this paper we examine antifragility, a complement to resilience and robustness, to manage the impulse response of complex cyber systems. Where fragile systems fracture when subjected to impulses, antifragile systems become stronger. We discuss why this strengthening characteristic makes antifragility attractive for managing impulse response in complex cyber systems and develop a measure for antifragility that differentiates it from fragility, resiliency and robustness. We then discuss an antifragile cyber system to demonstrate the benefits of antifragility in an impulse-rich environment.

Toward Risk-Informed Operation of Autonomous Vehicles to Increase Resilience in Unknown and Dangerous Environments

Operation of autonomous and semi-autonomous systems in hostile and expensive-to-access environments requires great care and a risk-informed operating mentality to protect critical system assets. Space exploration missions, such as the Mars Exploration Rover systems Opportunity and Curiosity, are very costly and difficult to replace. These systems are operated in a very risk-averse manner to preserve the functionality of the systems. By constraining system operations to risk-averse activities, scientific mission goals cannot be achieved if they are deemed too risky. We present a quantifiable method that increases the lifetime efficiency of obtaining scientific goals via the implementation of the Goal-Oriented, Risk Attitude-Driven Reward Optimization (GORADRO) method and a case study conducted with simulated testing of the method. GORADRO relies upon local area information obtained by the system during operations and internal Prognostics and Health Management (PHM) information to determine system health and potential localized risks such as areas where a system may become trapped (e.g.: sand pits, overhangs, overly steep slopes, etc.) while attempting to access scientific mission objectives through using an adaptable operating risk attitude. The results of our simulations and hardware validation using GORADRO show a large increase in the lifetime performance of autonomous rovers in a variety of environments, terrains, and situations given a sufficiently tuned set of risk attitude parameters. Through designing a GORADRO behavioral risk attitude set of parameters, it is possible to increase system resilience in unknown and dangerous environments encountered in space exploration and other similarly hazardous environments.

Feature Based Search of 3D Databases

This paper presents a novel algorithm “Twig Match” for feature based shape retrieval systems. The algorithm exploits recent advances in computational methods for subgraph isomorphism, in order to enable databases containing many thousands of components to be searched in less than a second. A face adjacency graph representation is created from a B-Rep model, allowing model comparison to be treated as a labelled subgraph isomorphism problem. This paper describes an experimental implementation which allows interactive specification of a target “feature”. By selectively including geometric filters, on faces and relations between neighbouring faces, the algorithm can ensure that matching topology is not incorrectly identified as matching geometry, while also offering users the ability to improve the precision of both query and results. Experimental results show that Twig Match accurately retrieves matching and similar sub-parts from collections at speeds suitable for interactive applications.

Reverse Engineering of Mechanical Parts: A Brief Overview of Existing Approaches and Possible New Strategies

Reverse Engineering (RE), also known as “CAD reconstruction”, aims at the reconstruction of 3D geometric models of objects/mechanical parts, starting from 3D measured data (points/mesh). In recent years, considerable developments in RE were achieved thanks to both academic and industrial research (e.g. RE software packages). The aim of this work is to provide an overview of state of the art techniques and approaches presented in recent years (considering at the same time tools and methods provided by commercial CAD software and RE systems). In particular, this article focuses on the “constrained fitting” approach, which considers geometrical constraints between the generated surfaces, improving the reconstruction result. On the basis of the overview, possible theoretical principles are drafted with the aim of suggest new strategies to make the CAD reconstruction process more effective in order to obtain more ready/usable CAD models. Finally, a new RE framework is briefly outlined: the proposed approach hypothesizes a tool built within the environment of an existing CAD system and considers the fitting of a custom-built archetypal model, defined with all the a-priori known dimensions and constraints, to the scanned data.

Networked, Real Time Translation of 3D Mesh Data to Immersive Virtual Reality Environments

Immersive virtual reality systems have the potential to transform the manner in which designers create prototypes and collaborate in teams. Using technologies such as the Oculus Rift or the HTC Vive, a designer can attain a sense of “presence” and “immersion” typically not experienced by traditional CAD-based platforms. However, one of the fundamental challenges of creating a high quality immersive virtual reality experience is actually creating the immersive virtual reality environment itself. Typically, designers spend a considerable amount of time manually designing virtual models that replicate physical, real world artifacts. While there exists the ability to import standard 3D models into these immersive virtual reality environments, these models are typically generic in nature and do not represent the designer’s intent. To mitigate these challenges, the authors of this work propose the real time translation of physical objects into an immersive virtual reality environment using readily available RGB-D sensing systems and standard networking connections. The emergence of commercial, off-the shelf RGB-D sensing systems such as the Microsoft Kinect, have enabled the rapid 3D reconstruction of physical environments. The authors present a methodology that employs 3D mesh reconstruction algorithms and real time rendering techniques to capture physical objects in the real world and represent their 3D reconstruction in an immersive virtual realilty environment with which the user can then interact. A case study involving a commodity RGB-D sensor and multiple computers connected through standard TCP internet connections is presented to demonstrate the viability of the proposed methodology.

Design and Implementation of Cyber-Physical Manufacturing Cloud Using MTConnect

Cyber-physical systems are gaining momentum in the domain of manufacturing. Cloud Manufacturing is also revolutionizing the manufacturing world. However, although there exist numerous physical manufacturing machines which are network-ready, very few of them are operated in a networked environment due to lack of scalability of existing cyber-physical systems. Combining the features offered by cloud manufacturing and cyber-physical systems, we develop a service-oriented architecture of scalable cyber-physical manufacturing cloud with MTConnect. A testbed of cyber-physical manufacturing cloud is being developed based on the above scalable architecture. In this system, manufacturing machines and their capabilities virtualized in a cyber-physical cloud. Manufacturing operations are represented as web services so that they are accessible across the Internet. Performance of the testbed of our cyber-physical manufacturing cloud with MTConnect is evaluated and test results show that our system achieves excellent service performance of manufacturing operations across Internet.