Collaborative Design Optimization Research Articles

Multidisciplinary Design and Collaborative Optimization for Excavator Backhoe Device

The excavator working device is a typical mechanical system of electromechanical liquid that is complex. Traditional optimization design methods are difficult to get global optimized results of excavator backhoe device through the serial mode of “mechanism-load-structure”. Thus, the theory of parallel collaborative optimization (CO) is applied. To establish a sophisticated CO model of the backhoe device, a certain excavator is investigated as a sample multidisciplinary CO (MDCO) design. To generate the CO model, an improved optimization algorithm called the particle swarm-genetic algorithm （PS-GA）is proposed. To verify the MDCO design of the excavator backhoe device, a parameterized virtual prototype (VP) of the backhoe device is established in ADAMS. This VP is optimized by applying the MDCO design results to the parameterized VP. The VP of the backhoe device is also optimized by a single discipline when the optimization results from a single discipline are inputted into the parameterized VP. Both optimized VPs are simulated under similar conditions, and results show that in the MDCO design, the arm crowd force of the backhoe device is 8.1% stronger than that in the design optimized by a single discipline under constant power and oil pressure conditions. Similarly, breakout force increased by approximately 8.3%. The quality (volume) of the entire backhoe device decreased by 9.5%; however, the maximum stress of each characteristic partition changed only slightly. Therefore, the MDCO design effectively and practically addresses problems regarding the optimization of the design of complex mechanical systems.

Collaborative Design Optimization of Main Movement System of Hydraulic Piston Engine

Hydraulic confined piston engine (HCPE) is a new type power device directly turning indicating work into hydraulic power, whose working process is related to many disciplines. The optimal design of its main movement system is very important for improving performance. Based on the minimum volume, the MDO model was constructed. The model includes systematic level optimizing model and disciplinary level optimizing model of crankshaft and connecting rod. Computed with collaborative optimization method, the total volume reduces by 12.62%, among which the volume of connecting rod increases by 9.26%, but crankshaft reduces by 14.06%. The result is more integrally optimal because of considering the collaborative effect between subsystems.

Research in Multidisciplinary Collaborative Optimization Base on Symmetric Fuzzy Satisfaction

Multidisciplinary collaborative optimization (CO) is a multi-level optimization algorithm, which include system-level and academic level. Because these are many complications in Engineering, it will exist the fuzzy in Discipline-level optimization devices. If the impact of discipline-level ambiguity was ignored, it will lead to some big errors in the system optimization. In order to solve this problem, this paper introduced the optimal fuzzy satisfaction into multidisciplinary collaborative optimization design, and made it as optimal targets of sub-discipline optimization devices. Then a method of multidisciplinary collaborative optimization base on Fuzzy Satisfaction was get., which can solve the fuzzy problem in multidisciplinary collaborative optimization. Meanwhile this paper used this method in multidisciplinary collaborative optimization of torpedo, and compared the results that was get by this method with the results which was get by the method that did not base on the fuzzy satisfaction, finally get the conclusion that the method is fit to Multidisciplinary collaborative optimization of torpedo.

Study on Mix-Variable Collaborative Design Optimization

In order to deal with complex product design optimization problems with both discrete and continuous variables, mix-variable collaborative design optimization algorithm is put forward based on collaborative optimization, which is an efficient way to solve mix-variable design optimization problems. On the rule of “divide and rule”, the algorithm decouples the problem into some relatively simple subsystems. Then by using collaborative mechanism, the optimal solution is obtained. Finally, the result of a case shows the feasibility and effectiveness of the new algorithm.

Vibration Characteristic Analysis and Collaborative Optimization Design for the Disk Brake

Patents record the continuous development of the disk brake. The disk brake is widely used as a brake device in the car and other vehicles. To enhance the braking stability of the disk brake, and acquire optimal structure parameters, we built the finite element (FE) models of the disk brake to conduct the constrained modal analysis; the first six order natural frequencies and vibration mode of each part were obtained, which indicated the third-order frequency of the friction disk and the second-order frequency of the caliper to be very close, easily leading to resonance of the system. The collaborative optimization was then carried out by using optimization algorithm; the optimal results showed the probability of the resonance to be reduced, where the braking stability of the system is enhanced.

Multi‐criteria decision making for collaborative design optimization of buildings

PurposeThe purpose of this paper is to improve current design processes by proposing a new approach based on multi‐criteria optimization of the designed asset. Management of design in construction projects is a complex task since it involves collaboration between professionals in multiple disciplines. Traditionally, designers work with a single solution at a time which is iteratively modified according to the view points of all the consultants. This results in sub‐optimal solutions. A multi‐criteria approach is able to accommodate diverse view points of specialist consultants in a construction project, aiming at a better optimized building system.Design/methodology/approachThe shortcomings of current design practices are analyzed based on a literature review. It is found that current approaches involving single objective optimization or Pareto optimization are not adequate for supporting collaborative design processes. A new approach to managing multiple objectives in design is proposed. This involves performing multi‐objective optimization, presenting a population of good solutions to the design consultants and selecting the best solution through an algorithm called RR‐PARETO2 (Relaxed‐Restricted Pareto) filtering. A software tool with a graphical user interface was developed. An example of the design of a building façade is taken to evaluate the application of this approach.FindingsThe paper provides empirical evidence that a multi‐objective optimization approach is able to provide support for the task of accommodating multiple viewpoints in design. The proposed methodology allows navigation through the solution space and pruning it visually by applying constraints. It is shown that the RR‐PARETO2 is able to select a good compromise solution with the best trade‐offs among all the objectives.Originality/valueThe idea of visualizing and filtering a population of design solutions has been proposed by design researchers for a long time, but is not currently adopted in practice in construction projects. The idea of collaborative filtering of the solution space according to the viewpoints of all the consultants by visually applying constraints on design variables and objectives is a new concept, the ultimate aim being a better balanced built asset. This is the first time the RR‐PARETO2 algorithm has been applied to building design.

111 分散環境下における協調設計フレームワークの構築

111 分散環境下における協調設計フレームワークの構築