1、 Ship Design Optimization This contribution is devoted to exploiting the analogy between a modern manufacturing plant and a heterogeneous parallel computer to construct a HPCN decision support tool for ship designers. The application is a HPCN one because of the scale of shipbuilding - a large conta
2、iner vessel is constructed by assembling about 1.5 million atomic components in a production hierarchy. The role of the decision support tool is to rapidly evaluate the manufacturing consequences of design changes. The implementation as a distributed multi-agent application running on top of PVM is
3、described 1 Analogies between Manufacturing and HPCN There are a number of analogies between the manufacture of complex products such as ships, aircraft and cars and the execution of a parallel program. The manufacture of a ship is carried out according to a production plan which ensures that all th
4、e components come together at the right time at the right place. A parallel computer application should ensure that the appropriate data is available on the appropriate processor in a timely fashion. It is not surprising, therefore, that manufacturing is plagued by indeterminacy exactly as are paral
5、lel programs executing on multi-processor hardware. This has caused a number of researchers in production engineering to seek inspiration in other areas where managing complexity and unpredictability is important. A number of new paradigms, such as Holonic Manufacturing and Fractal Factories have em
6、erged 1,2 which contain ideas rather reminiscent of those to be found in the field of Multi- Agent Systems 3, 4. Manufacturing tasks are analogous to operations carried out on data, within the context of planning, scheduling and control. Also, complex products are assembled at physically distributed
7、 workshops or production facilities, so the components must be transported between them. This is analogous to communication of data between processors in a parallel computer, which thus also makes clear the analogy between workshops and processors. The remainder of this paper reports an attempt to e
8、xploit this analogy to build a parallel application for optimizing ship design with regard to manufacturing issues. 2 Shipbuilding at Odense Steel Shipyard Odense Steel Shipyard is situated in the town of Munkebo on the island of Funen. It is recognized as being one of the most modern and highly aut
9、omated in the world. It specializes in building VLCCs (supertankers) and very large container ships. The yard was the first in the world to build a double hulled supertanker and is currently building an order of 15 of the largest container ships ever built for the Maersk line. These container ships
10、are about 340 metres long and can carry about 7000 containers at a top speed of 28 knots with a crew of 12. Odense Steel Shipyard is more like a ship factory than a traditional shipyard. The ship design is broken down into manufacturing modules which are assembled and processed in a number of worksh
11、ops devoted to, for example, cutting, welding and surface treatment. At any one time, up to 3 identical ships are being built and a new ship is launched about every 100 days. The yard survives in the very competitive world of shipbuilding by extensive application of information technology and robots
12、, so there are currently about 40 robots at the yard engaged in various production activities. The yard has a commitment to research as well, so that there are about 10 industrial Ph.D. students working there, who are enrolled at various engineering schools in Denmark. 3 Tomorrows Manufacturing Syst
13、ems The penetration of Information Technology into our lives will also have its effect in manufacturing industry. For example, the Internet is expected to become the dominant trading medium for goods. This means that the customer can come into direct digital contact with the manufacturer. The direct
14、 digital contact with customers will enable them to participate in the design process so that they get a product over which they have some influence. The element of unpredictability introduced by taking into account customer desires increases the need for flexibility in the manufacturing process, es
15、pecially in the light of the tendency towards globalization of production. Intelligent robot systems, such as AMROSE, rely on the digital CAD model as the primary source of information about the work piece and the work cell 5,6.This information is used to construct task performing, collision avoidin
16、g trajectories for the robots, which because of the high precision of the shipbuilding process, can be corrected for small deviations of the actual world from the virtual one using very simple sensor systems. The trajectories are generated by numerically solving the constrained equations of motion f
17、or a model of the robot moving in an artificial force field designed to attract the tool centre to the goal and repell it from obstacles, such as the work piece and parts of itself. Finally, there are limits to what one can get a robot to do, so the actual manufacturing will be performed as a collab
18、oration between human and mechatronic agents. Most industrial products, such as the windmill housing component shown in Fig. 1, are designed electronically in a variety of CAD systems. Fig. 1. Showing the CAD model for the housing of a windmill. The model, made using Bentley Microstation, includes b
19、oth the work-piece and task-curve geometries. 4 Todays Manufacturing Systems The above scenario should be compared to todays realities enforced by traditional production engineering philosophy based on the ideas of mass production introduced about 100 years ago by Henry Ford. A typical production line has the same structure as a serial computer program, so that the whole process is driven by production requirements. This rigidity is reflected on the types of top-down planning and control systems used in manufacturing industry, which are badly suited to both complexity and unpredictability.
