A Software Framework For Intelligent Computer-Automated Product Design

Abstract

For many years, NTNU in Ålesund (formerly Aalesund University College) has maintained a close relationship with the maritime industrial cluster, centred in the surrounding geographical region, thus acting as a hub for both education, research, and innovation. Of many common relevant research topics, virtual prototyping is currently one of the most important. In this paper, we describe our first complete version of a generic and modular software framework for intelligent computer-automated product design. We present our framework in the context of design of offshore cranes, with easy extensions to other products, be it maritime or not. Funded by the Research Council of Norway and its Programme for Regional R&D and Innovation (VRI), the work we present has been part of two separate but related research projects (grant nos. 241238 and 249171) in close cooperation with two local maritime industrial partners.We have implemented several software modules that together constitute the framework, of which the most important are a server-side crane prototyping tool (CPT), a client-side web graphical user interface (GUI), and a client-side artificial intelligence for product optimisation (AIPO) module that uses a genetic algorithm (GA) library for optimising design parameters to achieve a crane design with desired performance. Communication between clients and server is achieved by means of the HTTP and WebSocket protocols and JSON as the data format.To demonstrate the feasibility of the fully functioning complete system, we present a case study where our computer-automated design was able to improve the existing design of a real and delivered 50-tonnes, 2.9 million EUR knuckleboom crane with respect to some chosen desired design criteria.Our framework being generic and modular, both clientside and server-side modules can easily be extended or

Grey wolf optimizer (GWO) for automated offshore crane design

“…A. Client-Server Architecture The diagram in Fig. 3 shows the client-server architecture of our software framework (adapted from [6]). On the serverside, the CPT contains a product (in this case, an offshore crane) calculator able to calculate a number of KPIs of a specified crane design based on a set of about 120 design parameters.…”

“…Here, the MCOC connect to the CPT via WS/JSON. Messages are sent as JSON objects in a standardized format that the CPT accepts, consisting of three parts (sub-objects) [6]:…”

“…We have previously developed a computer-automated design (CautoD) software framework for product design optimization and tested it on the design of offshore cranes [5][6][7][8]. The framework has several components.…”

“…A client-side web graphical user interface (GUI) facilitates the process of manually selecting the design parameters in the CPT to obtain a simple visualization of the designed crane and its 2D safe working load (SWL) chart [5]. For design optimization, we have developed a client-side product optimization client, namely the Artificial Intelligence for Product Optimization (AIPO) module that uses a genetic algorithm (GA) for optimizing the design parameters in a manner that achieves the crane's desired design criteria (e.g., KPIs related to performance and cost specifications) [6]. Complementing the AIPO module, we have also implemented a Matlab ® software module, the Matlab ® crane optimization client (MCOC), that also used a GA for single and multiobjective optimization [7].…”

Intelligent Computer-Automated Crane Design Using An Online Crane Prototyping Tool

“…241238 and 249171) for using artificial intelligence (AI) for intelligent computer-automated design (CautoD) of offshore cranes and winches, respectively. In an accompanying paper submitted concurrently (Bye et al, 2016), we present our first complete version of a generic and modular software framework for intelligent computerautomated product design. The framework has been implemented with a client-server software architecture for the design of offshore cranes and consists of several modules: a server-side crane prototyping tool (CPT); a client-side web graphical user interface (GUI); and a client-side artificial intelligence for product optimisation (AIPO) module that uses a genetic algorithm (GA) for optimisation.…”