Manufacturing compliance analysis for architectural design: a knowledge-aided feature-based modeling framework

Given that achieving nominal (all dimensions are theoretically perfect) geometry is challenging during building construction, understanding and anticipating sources of geometric variation through tolerances modeling and allocation is critical. However, existing building modeling environments lack the ability to support coordinated, incremental and systematic specification of manufacturing and construction requirements. This issue becomes evident when adding multi-material systems produced off site by different vendors during building erection. Current practices to improve this situation include costly and time-consuming operations that challenge the relationship among the stakeholders of a project. As one means to overcome this issue, this research proposes the development of a knowledge-aided modeling framework that integrates a parametric CAD tool with a system modeling application to assess variability in building construction. The CAD tool provides robust geometric modeling capabilities, while System Modeling allows for the specification of feature-based manufacturing requirements aligned with construction standards and construction processes know-how. The system facilitates the identification of conflicting interactions between tolerances and manufacturing specifications of building material systems. The expected contributions of this project are the representation of manufacturing knowledge and tolerances interaction across off-site building subsystems to identify conflicting manufacturing requirements and minimize costly construction errors. The proposed approach will store and allocate manufacturing knowledge as Model-Based Systems Engineering (MBSE) design specifications for both single and multiple material systems. Also, as new techniques in building design and construction are beginning to overlap with engineering methods and standards (e.g. in-factory prefabrication), this project seeks to create collaborative scenarios between MBSE and Building Information Modeling (BIM) based on parametric, simultaneous, software integration to reduce human-to-data translation errors, improving model consistency among domains. Important sub-stages of this project include the comprehensive review of modeling and allocation of tolerances and geometric deviations in design, construction and engineering; an approach for model integration among System Engineering models, mathematical engines and BIM (CAD) models; and finally, a demonstration computational implementation of a System-level tolerances modeling and allocation approach.Ph.D

Towards 2D Traceability in a Platform for Contract Aware Visual Transformations with Tolerated Inconsistencies

Today's model-driven engineering tools focus on the automatic transformation of software models and lack essential support for interacting with developers. This paper presents some lessons learned from building a standard compliant platform for the visual development of interactive consistency maintenance software. Based on an established requirements engineering case study, the paper illustrates the need for developer interaction and the controlled tolerance of inconsistencies. This motivates the role of traceability links in two dimensions: links between application models allow one to maintain consistency incrementally and tolerate inconsistencies in a controlled manner. In the other dimension, links between transformation models enable the refinement of declarative descriptions of consistency contracts into constructive transformations. Such transformations can be generated automatically from the contracts but tend to be optimized subtly by a transformation expert

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

Supply chain visibility and sustainable competitive advantage: An integrated model

Lack of visibility of the assets in a product supply chain compromises attempts to optimise supply chain management. Increasing the visibility of these assets presents a relatively unexplored frontier in operations and supply where organisations can create competitive advantage through the opportunities asset visibility offer. This research aims at investigating the key capabilities of asset visibility specifically those associated with returnable transport assets that travel across supply chains carrying material and products e.g. cages, boxes, trays, trolleys and pallet bins. In addition, how these capabilities may influence supply chain visibility and firm performance in a way that might lead to sustainable competitive advantage is examined. To achieve these objectives, the research develops a two-stage model that is theoretically grounded in the extended resource-based view. Philosophically, the research adopts a critical realist approach using abductive logic. Methodologically, a sequential exploratory strategy for data collection is implemented. A qualitative, indepth site-based case study supported by field expert interviews was conducted as a pilot study. The pilot study findings refined the initial conceptual model derived from literature and informed the next stage of the research. The quantitative phase focused on refining the factors constituting asset visibility capabilities and then testing the relationship between these capabilities and supply chain visibility, performance and sustainable competitive advantage. Key findings are that asset visibility capabilities are shaped through three key capabilities: (1) an asset management capability formed by both core technological aspects related to tracking and tracing technology, and non-technological ones focusing on logistic-related capability; (2) a complementary technological capability comprising of IT infrastructure for supply chain integration; and (3) a complementary nontechnological capability represented through three sub-capabilities: (a) supply chain process integration; (b) focal firm-3PL relational orientation; and (c) internal firm integration. The research findings prove a positive relationship between asset visibility capabilities and supply chain visibility. In addition, a positive relationship between these capabilities and sustainable competitive advantage through the mediated effect of supply chain visibility and firm performance, is confirmed.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Text Similarity Between Concepts Extracted from Source Code and Documentation

Context: Constant evolution in software systems often results in its documentation losing sync with the content of the source code. The traceability research field has often helped in the past with the aim to recover links between code and documentation, when the two fell out of sync. Objective: The aim of this paper is to compare the concepts contained within the source code of a system with those extracted from its documentation, in order to detect how similar these two sets are. If vastly different, the difference between the two sets might indicate a considerable ageing of the documentation, and a need to update it. Methods: In this paper we reduce the source code of 50 software systems to a set of key terms, each containing the concepts of one of the systems sampled. At the same time, we reduce the documentation of each system to another set of key terms. We then use four different approaches for set comparison to detect how the sets are similar. Results: Using the well known Jaccard index as the benchmark for the comparisons, we have discovered that the cosine distance has excellent comparative powers, and depending on the pre-training of the machine learning model. In particular, the SpaCy and the FastText embeddings offer up to 80% and 90% similarity scores. Conclusion: For most of the sampled systems, the source code and the documentation tend to contain very similar concepts. Given the accuracy for one pre-trained model (e.g., FastText), it becomes also evident that a few systems show a measurable drift between the concepts contained in the documentation and in the source code.</p