Research On The Shipyard Hoisting Process Digital Modelling And Simulation

Shipyard hoisting process exists in a lot of shipbuilding lifecycle processes,the erection hoisting process occurred in the dock shop is the most complex one due to its project-type manufacturing characteristics.Considering that the hoisting process can hardly apply automatic technology,the most feasible and promising way to improve efficiency is introducing digital manufacturing technology.However,previous researches regarding digital hoisting process lacked a systematic view to decompose,describe,optimize and simulate this process.On the other hand,the particular feature of the erection hoisting process makes it very difficult to apply modelling and simulation methods achieved in other manufacturing processes.Therefore,with the goals of getting insight of structural and dynamic characteristics of the hoisting process,then creating effective digital manufacturing method for this kind of process,the key academic problems are concluded and solved under the guidance of relevant theories.The process modelling method research,process planning method research,production scheduling research and production system simulation research are carried out.At first,the erection hoisting process modelling method is studied.After investigating the hoisting process’s components and their relationships thoroughly and systematically,a novel modelling method with multi-view,task-centric structure named T-PARS is proposed suitable for the project-type manufacturing process,the framework,components,and syntax of TPARS method is explained with the form of meta model.The T-PARS method achieves horizontal integration of different functions and organizations through its task view with three dimensions of section,stage and type.The vertical ingeration between management and manufacturing is also realized by the activity view in which the information activity and working activity are integrated.As a result,the complicated requirement of working flow,information flow and control flow description of hoisting process is well reflected by the TPARS method,so the hositing process model built by T-PARS method provides a common,consistent,and complete reference for various digital manufacturing technology researches.In the end,a case study with T-PARS method is carried out using a commercial modelling tool.Based on the characteristics revealed by the T-PARS model,the computer-aided hoisting process design method is further researched to sovle the problems of design process modelingl,design process reengineering,and process data modelling.According to the concurrent,integrating,collaborative concept of Computer Aided Process Planning technology,the process planning scope is obtained from T-PARS model to support extracting the hoisting process planning activities and their relationships,a data flow diagram is therewith established as the design process model.Then the structure of design process is reengineered by a series of design structure matrix manipulations,so as to provide the foundation of multi-professional collaborative work.A hoisting process data model is constructed with Merise method in accordance with the data structure of design process model,thereby downstream digital manufacturing applications are able to acquire consistent,single data source to carry out their fundtions.In the end,a computer-aided hoisting process planning prototype is developed through which a case study is performed to demonstrate the effect of proposed hoisting process design method.As for the production management stage,the hoisting preparing stage scheduling problem is researched due to its hybrid feature and high calculation complexity.The particular characteristics of hoisting preparing stage scheduling is analyzed based on production scheduling theory,then a mathematic model is constructed following the process route and resource constraint presented by the T-PARS model.On this basis,a superior heuristic algorithm and an improved hybird meta-heuristic algorithm are invented to search relatively optimal solution of hoisting preparing stage scheduling.The proposed heuristic algorithm exploits diverse relationships between jobs and resources to search potentially better solutions in more effective way than general heuristic algorithms which usually produce quite normal solutions due to their shortages of limited searching space and simple decision rules.The proposed meta-heuristic algorithm is devised using the basic framework of Genetic Algorithm,its highlight lies in the new mutation stategy with 5 mutation rules based on the discovery of non-bottleneck tasks’ interval shrinking mechanism and conditions that can make bottleneck tasks finished earlier,as a result,much higher efficiency can be achieved in every calculating iteration and more splendid solutions can be acquired at the same time.Considering the large scale,complicated scheduling deadlocks that apprear in the execution of meta-heruistic altorithm,classification of deadlocks and their nesting relationships are rigorously discussed with Graph Theroy,thus a minimum cost unlocking strategy is come up with focusing on the shortest and largest shared deadlock chains.With the help of proposed deadlock handling algorithm,all the deadlocks can be efficiently eliminated and synchronously avoiding population homogeneous disadvantage that existing algorithms possess.At last,the proposed three algorithms are implemented with computer programme to carry out a case study using a group of actual hoisting preparing stage scheduling problem.After getting results of hoisting process planning and hoisting procution scheduling,the hoisting production system simulation is researched,solving the problems of simulation modelling and simulation algorithm.At first,the specific requirements of hoisting production system simulation are scientifically concluded.Following the theory of Discrete Event Simulation,the components of T-PARS model are investigated to determine which should be abstracted in the simulation model,then an information flow and work flow integrated simulation modelling method named IWI is put forward in form of hierarchical Petri net,reflecting dynamic behavior of practical hoisting production.A simulation algorithm based on Process Interactive concept is put forward in accordance with the structure of IWI model,the algorithm is able to effectively respond to the heavy burdens of handling large amounts of entities that brought by IWI model.Moreover,the algorithm possesses plan-driven logic instead of rule-based logic to fulfill special demand of project-type production system simulation.The proposed IWI model and simulation algorithm are realized with a developed simulation prototype,through which a verification experiment is conducted using a group of dock shop hoisting production plans,outputting several indices to evaluate performance of production system and to figure out how to optimize initial production plan.The adjusted plan is simulated to get comparison with the result of initial plan,achieving the goals of simulation-based predicting,evaluating and optimizing.These works provide an essential foundation to realize predictable manufacturing for the dock shop hoisting process instead of traditional experiencebased manufacturing.