An Overview of Concurrent Engineering Research and Its Industrial Implementation in Chinese Enterprises

Concurrent Engineering (CE) is an effective way for enterprises to reengineer the product development processes and to improve the product development abilities. In this paper, the existing status of product development in Chinese manufacturing industry is analyzed, and the requirements of manufacturing technology for them are investigated. An overview of our CE R&D work is introduced, including product modeling, DFA, DFM, QFD, PDM, and other enabling technologies. A case study of the CE pilot project is discussed. The industrial implementation and application in Chinese enterprises are summarized.

Product Development Process Simulation for Concurrent Engineering

The simulation of a product development process for concurrent engineering has beenmotivated by the desire to increase productivity by improving the product development pro-cess.In this paper,the IDEF3 process description capture method is discussed.On the basisof IDEF3 method,a simulation system of the product development process for concurrent en-gineering is developed.The architecture of the simulation system is proposed.The simula-tion model is built using object-oriented approach.It employs an event scheduling approachto emulate the product development process.The simulation mechanism based on messagepassing:is also presented.

Robust Collaborative Optimization Method Based on Dual-response Surface

A novel method for robust collaborative design of complex products based on dual-response surface （DRS-RCO） is proposed to solve multidisciplinary design optimization （MDO） problems under uncertainty. Collaborative optimization （CO） which decomposes the whole system into a double-level nonlinear optimization problem is widely accepted as an efficient method to solve MDO problems. In order to improve the quality of complex product in design process, robust collaborative optimization （RCO） is developed to solve those problems under uncertain conditions. RCO does optimization on the linear sum of mean and standard deviation of objective function and gets an optimal solution with high robustness. Response surfaces method is an important way to do approximation in robust design. DRS-RCO is an improved RCO method in which dual-response surface replaces system uncertainty analysis module of CO. The dual-response surface is the approximate model of mean and standard deviation of objective function respectively. In DRS-RCO, All the information of subsystems is included in dual-response surfaces. As an additional item, the standard deviation of objective function is added to the subsystem optimization. This item guarantee both the mean and standard deviation of this subsystem is reaching the minima at the same time. Finally, a test problem with two coupled subsystems is conducted to verify the feasibility and effectiveness of DRS-RCO.

GREEDY NON-DOMINATED SORTING IN GENETIC ALGORITHM-ⅡFOR VEHICLE ROUTING PROBLEM IN DISTRIBUTION

Vehicle routing problem in distribution （VRPD） is a widely used type of vehicle routing problem （VRP）, which has been proved as NP-Hard, and it is usually modeled as single objective optimization problem when modeling. For multi-objective optimization model, most researches consider two objectives. A multi-objective mathematical model for VRP is proposed, which considers the number of vehicles used, the length of route and the time arrived at each client. Genetic algorithm is one of the most widely used algorithms to solve VRP. As a type of genetic algorithm （GA）, non-dominated sorting in genetic algorithm-Ⅱ （NSGA-Ⅱ） also suffers from premature convergence and enclosure competition. In order to avoid these kinds of shortage, a greedy NSGA-Ⅱ （GNSGA-Ⅱ） is proposed for VRP problem. Greedy algorithm is implemented in generating the initial population, cross-over and mutation. All these procedures ensure that NSGA-Ⅱ is prevented from premature convergence and refine the performance of NSGA-Ⅱ at each step. In the distribution problem of a distribution center in Michigan, US, the GNSGA-Ⅱ is compared with NSGA-Ⅱ. As a result, the GNSGA-Ⅱ is the most efficient one and can get the most optimized solution to VRP problem. Also, in GNSGA-Ⅱ, premature convergence is better avoided and search efficiency has been improved sharply.

Study on an Configuration Framework for Product Family

In implementing mass customization, how to respond rapidly to customers’ requirements is a key problem. Configuration design is considered effective in early stage of product design. This paper studies a configuration method based on constraints and fuzzy decision for product family. The configuration method is evolved from constraint based product configuration. It employs fuzzy optimum selection in the reasoning process, which can select similar components when customers’ requirements can not be met precisely. In the configurator, product family is represented with GBOM(Generic Bill Of Material) and ACL(Article Characteristic List). Every node of GBOM has an ACL to list all instances of a component family. Constraints are attached to every node, which involves variable definition and constraints definition. In the reasoning process, constraint satisfaction and fuzzy optimum selection interact to search optimum solution. A prototype is developted to demonstrate how to run the configurator. The paper ends with a discussion of advantages, future work of the configuration method.

Intelligent Multilevel Knowledge Acquisition System for Product Design and Its Implementation

The characteristics of design process, design object and domain knowledge of complex product are analyzed. A kind of knowledge representation schema based on integrated generalized rule is stated. An AND-OR tree based model of concept for domain knowledge is set up. The strategy of multilevel domain knowledge acquisition based on the model is presented. The intelligent multilevel knowledge acquisition system (IMKAS) for product design is developed, and it is applied in the intelligent decision support system of concept design of complex product.

An extended HLA multilayer federation integration architecture for multidisciplinary collaborative simulation

The development of complex products is essentially concerned with multidisciplinary knowledge.Running on Internet, integration based on multilayer federation architecture and dynamic reuse of simulationresources are the major difficulties for complex product collaborative design and simulation. Since thetraditional Run-Time Infrastructure (RTI) is not good at supporting these new requirements, an extendedhigh level architecture (HLA) multilayer federation integration architecture (MLFIA), based on the resourcemanagement federation (RMF) and its supporting environment based Service-oriented architecture(SOA) and HLA (SOHLA) are proposed, The idea and realization of two key technologies, the dynamiccreation of simulation federation based on RMF, TH_RTT, an extensible HLA runtime infrastructure(RTI), used at Internet are emphasized. Finally, an industry case about multiple unit (MU) is given.

Applying Object-oriented Simulation to the Development of FMS Control Software

The approach of control software development based on simulation is discussed. A library of object classes for a flexible manufacturing system(FMS) simulation has been developed using the technology of object-oriented programming. Using the library, the simulation software of a FMS which has the same manufacturing logic with the FMS control system can be easily constructed. A new approach in the development of FMS control software based on software reuse and an emulator of the blade FMS control system for testing control software have also been developed.

Formal Verification of Temporal Properties for Reduced Overhead in Grid Scientific Workflows

With quick development of grid techniques and growing complexity of grid applications, it is becoming critical for reasoning temporal properties of grid workflows to probe potential pitfalls and errors, in order to ensure reliability and trustworthiness at the initial design phase. A state Pi calculus is proposed and implemented in this work, which not only enables fexible abstraction and management of historical grid verification of grid workflows. Furthermore, a relaxed region system events, but also facilitates modeling and temporal analysis （RRA） approach is proposed to decompose large scale grid workflows into sequentially composed regions with relaxation of parallel workflow branches, and corresponding verification strategies are also decomposed following modular verification principles. Performance evaluation results show that the RRA approach can dramatically reduce CPU time and memory usage of formal verification.

Performance Improvement of Distributed Systems by Autotuning of the Configuration Parameters

The performance of distributed computing systems is partially dependent on configuration parameters recorded in configuration files. Evolutionary strategies, with their ability to have a global view of the structural information, have been shown to effectively improve performance. However, most of these methods consume too much measurement time. This paper introduces an ordinal optimization based strategy combined with a back propagation neural network for autotuning of the configuration parameters. The strat- egy was first proposed in the automation community for complex manufacturing system optimization and is customized here for improving distributed system performance. The method is compared with the covariance matrix algorithm. Tests using a real distributed system with three-tier servers show that the strategy reduces the testing time by 40% on average at a reasonable performance cost.

An Interactive Assembly Process Planner

This paper describes the implementation and performance of the virtual assembly support sys-tem (VASS), a new system that can provide designers and assembly process engineers with a simulation and visualization environment where they can evaluate the assemblability/disassemblability of products, and thereby use a computer to intuitively create assembly plans and interactively generate assembly process charts. Subassembly planning and assembly priority reasoning techniques were utilized to find heuristic information to improve the efficiency of assembly process planning. Tool planning was imple-mented to consider tool requirements in the product design stage. New methods were developed to reduce the computation amount involved in interference checking. As an important feature of the VASS, human interaction was integrated into the whole process of assembly process planning, extending the power of computer reasoning by including human expertise, resulting in better assembly plans and better designs.

A dynamic delivery strategy for material handling in mixed-model assembly lines using decentralized supermarkets

Material handling has become one of the major challenges in modern production management.Consequently,this paper intends to investigate the part delivery of mixedmodel assembly lines with decentralized supermarkets and tow trains.Besides,uncertain exception disturbances,including tow train failures and adjustments of the production sequence,are also considered.To solve this problem,a heuristic-based dynamic delivery strategy is proposed,which dynamically schedules the route,departure time,quantities and types of loaded parts for each tour.To evaluate the performance of this strategy,it is used to solve an instance in comparison with the periodic delivery strategy,experimental results are reported and their performances are compared under different metrics.Moreover,a multi-scenario analysis is employed to determinate the long-term decisions,including the number of tow trains and the route layout.Finally,the critical storage is suggested to be set for each station to avoid part starvation resulting from disturbances,and its effect on the delivery performance is investigated.

Adaptive scheduling method for dynamic robotic cell based on pattern classification algorithm

In order to deal with the dynamic production environment with frequent fluctuation of processing time,robotic cell needs an efficient scheduling strategy which meets the real-time requirements.This paper proposes an adaptive scheduling method based on pattern classification algorithm to guide the online scheduling process.The method obtains the scheduling knowledge of manufacturing system from the production data and establishes an adaptive scheduler,which can adjust the scheduling rules according to the current production status.In the process of establishing scheduler,how to choose essential attributes is the main difficulty.In order to solve the low performance and low efficiency problem of embedded feature selection method,based on the application of Extreme Gradient Boosting model(XGBoost)to obtain the adaptive scheduler,an improved hybrid optimization algorithm which integrates Gini impurity of XGBoost model into Particle Swarm Optimization(PSO)is employed to acquire the optimal subset of features.The results based on simulated robotic cell system show that the proposed PSO-XGBoost algorithm outperforms existing pattern classification algorithms and the newly learned adaptive model can improve the basic dispatching rules.At the same time,it can meet the demand of real-time scheduling.

Simulation-oriented model reuse in cyber-physical systems: A method based on constrained directed graph

Modeling and Simulation of Cyber-Physical Systems(MSCPS)is demanding in terms of immediate response to dynamic and complex changes of CPS.Simulation-oriented model reuse can be used to build a whole CPS model by reusing developed models in a new sim-ulation application,which avoid repeated modeling and thus reduce the redevelopment of submodels.Model composition,one of the important methods,enables model reuse by selecting and adopting diversified integration solutions of simulation components to meet the requirements of simulation application systems.In this paper,a real-time model integration approach for global CPS modeling is proposed,which reuses devel-oped submodels by compositing submodel nodes.Specifically,a constrained directed graph of submodels for the whole system which can meet the simulation requirements is constructed by reverse matching.Submodel properties,including co-simulation distance between submodel nodes,reuse benefit and simulation performance of model nodes,are quantified.Based on the properties,the model-integrated solution for the whole CPS simulation is retrieved throughout the model constrained digraph by the Genetic Algo-rithm(GA).In the experiment,the proposed method is applied to a typical model integrated computing scenario containing multiple model-integration solutions,among which the Pareto optimal solutions are retrieved.Results show that the effectiveness of the model integration method proposed in this paper is verified.

Knowledge-driven material design platform based on the whole-process simulation and modeling

In order to realize the agility,collaboration and visualization of alloy material devel-opment process,a product development platform based on simulation and modeling technologies is established in this study.In this platform,the whole-process simulation module builds multi-level simulation models based on metallurgical mechanisms from the production line level,the thermo-mechanical coupling field level and the microstructure evolution level.The design knowledge management module represents the multi-source heterogeneous material design knowledge through ontology model,including customers’requirement knowledge,material component knowledge,process design knowledge and quality inspection knowledge,and utilizes the case-based reasoning approach to reuse the knowledge.The data-driven modeling module applies machine learning algorithms to mine the relationships between product mechanical properties,material components,and process parameters from historical samples,and utilizes multi-objective optimiza-tion algorithms to find the optimal combination of process parameters.Application of the developed platform in actual steel mills shows that the proposed method helps to improve the efficiency of product design process.