船舶专业外文翻译一船舶设计优化Ship Design OptimizationThis 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 container 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 described1 Analogies between Manufacturing and HPCNThere 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 the 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 parallel 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 emerged [1,2] which contain Ideas rather reminiscent of those to be found inthe 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 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 exploit this analogy to build a parallel application for optimizing ship design with regard to manufacturing issues.2 Shipbuilding at Odense Steel ShipyardOdense 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 automated in the world. Itspecializes in building VLCC's (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 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 workshops 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, so there are currently about 40 robots at the yard engaged in various production activities. The yard has a coininitment 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 Tomorrow's Manufacturing SystemsThe penetration of Information Technology into our lives will also have its effect in manufacturing Industry. For example, the Internet is expected to becomethe dominant trading medium for goods. This means that the customer can come Into direct digital contact with the manufacturer.The direct 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, especially in the light of the tendency towards globalization of productioiLIntelligent 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 avoiding 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 ven r simple sensor systems. The trajectories are generated by numerically solving the constrained equations of motion for 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 collaboration 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 both the work-piece and task-curve geometries.4 Today v s Manufacturing SystemsThe above scenario should be compared to today's 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.In fact, the manufacturing environment has always been characterized by unpredictability. Today's manufacturing systems are based on idealized models where unpredictability is not taken into account but handled using complex and expensive logistics and buffering systems.Manufacturers are also becoming aware that one of the results of the top-down serial approach is an alienation of human workers. For example, some of the car manufacturers have experimented with having teams of human workers responsible for a particular car rather than performing repetitive operations in a production line. This model in fact better reflects the concurrency of the manufacturing process than the assembly line.5 A Decision Support Tool for Ship Design OptimizationLarge ships are, together with aircraft, some of the most complex things ever built A container ship consists of about 1.5 million atomic components which are assembled in a hierarchy of increasingly complex components. Thus any support tool for the manufacturing process can be expected to be a large HPCN application.Ships are designed with both functionality and ease of construction in mind, as well as issues such as economy, safety, insurance issues, maintenance and even decommissioning. Once a functional design is in place, a stepwise decomposition of the overall design into a hierarchy of manufacturing components is performed. The manufacturing process then starts with the individual basic building blocks such as steel plates and pipes. These building blocks are put together into ever more complex structures and finally assembled in the dock to form the flnished ship.Thus a very useful thing to know as soon as possible after design time are the manufacturing consequences of design decisions. This includes issues such as whether the intermediate structures can actually be built bv the availableproduction facilities, the implications on the use of material and whether or not the production can be efficiently scheduled [7].Fig.2. shows schematically how a redesign decision at a point in time during construction implies future costs, only some of which are known at the time. Thus a decision support tool is required to give better estimates of the implied costs as early as possible in the process.Simulation，both of the feasibility of the manufacturing tasks and the efficiency with which these tasks can be performed using the available equipment, is a very compute-intense application of simulation and optimization. In the next section, we describe how a decision support tool can be designed and implemented as a parallel application by modeling the main actors in the process as agents.Fig>2> Economic consequences of design decisions. A design decision implies a future commitment of economic resources which is only partially known at design time.6 Multi-Agent SystemsThe notion of a software agent, a sort of autonomous, dynamic generalization of an object (in the sense of Object Orientation) is probably unfamiliar to the typical HPCN reader in the area of scientific computation. An agent possesses its own beliefs, desires and intentions and is able to reason about and act oil its perceptionof other agents and the environment.A multi-agent system is a collection of agents which try to cooperate to solve some problem, typically in the areas of control and optimization. A good example is the process of learning to drive a car in traffic. Each driver is an autonomous agent which observes and reasons about the intentions of other drivers. Agents are in fact a very useful tool for modeling a wide range of dynamical processes in the real worlds such as the motion of protein molecules [8] or multi-link robots [9]. For other applications, see [4].One of the interesting properties of multi-agent systems is the way global behavior of the system emerges from the individual interactions of the agents [10]. The notion of emergence can be thought of as generalizing the concept of evolution in dynamical systems.Examples of agents present in the system are the assembly network generator agent which encapsulates knowledge about shipbuilding production methods for planning assembly sequences, the robot motion verification agent, which is a simulator capable of generating collision-free trajectories for robots carrying out their tasks, the quantity surveyor agent which possesses knowledge about various costs involved in the manufacturing process and the scheduling agent which designs a schedule for performing the manufacturing tasks using the production resources available.7 Parallel ImplementationThe decision support tool which implements all these agents is a piece of Object- Oriented software targeted at a multi-processor system, in this case, a network of Silicon Graphics workstations in the Design Department at Odense Steel Shipyard. Rather than hand-code all the communication between agents and meta-code for load balancing the parallel application, abstract interaction mechanisms were developed. These mechanisms are based on a task distribution agent being present on each processor. The society of task distribution agents is responsible for all aspects of communication and migration of tasks in the system.The overall agent system runs on top of PVM and achieves good speedup and load balancing. To give some idea of the size of the shipbuilding application^ it takes 7 hours to evaluate a single design on 25 SGI workstations.From：Applied Parallel Computing Large Scale Scientific and Industrial Problems LectureNotes in Computer Science, 1998, Volume1541/199& 476-482, DOI: 10.1007/BFb0095371.中文翻译：船舶设计优化这一贡献致力于开拓类比现代先进制造工厂和一个异构并行计算机，构建了一种HPCN决策支援工具给船舶设计师。