Tianyuan Xiao

Strategic robust mixed model assembly line balancing based on scenario planning

Abstract Assembly line balancing involves assigning a series of task elements to uniform sequential stations with certain restrictions. Decision makers often discover that a task assignment which is optimal with respect to a deterministic or stochastic/fuzzy model yields quite poor performance in reality. In real environments, assembly line balancing robustness is a more appropriate decision selection guide. A robust model based on the α worst case scenario is developed to compensate for the drawbacks of traditional robust criteria. A robust genetic algorithm is used to solve the problem. Comprehensive computational experiments to study the effect of the solution procedure show that the model generates more flexible robust solutions. Careful tuning the value of α allows the decision maker to balance robustness and conservativeness of assembly line task element assignments.

Balancing and sequencing of stochastic mixed-model assembly U-lines to minimise the expectation of work overload time

A mixed-model assembly U-line is a flexible production system capable of manufacturing a variety of similar models, and it has become popular as an important component of the just-in-time production system. However, it poses new challenges for the optimal design of assembly lines because both the task assignment and the production sequence affect the workload variance among workstations. As a consequence, this paper addresses the line balancing problem and the model sequencing problem jointly and proposes a 0–1 stochastic programming model. In this model, task times are assumed to be stochastic variables independently distributed with normal distributions and the objective is to minimise the expectation of work overload time for a given combination of cycle time and number of workstations. To solve the problem, a simulated annealing-based algorithm is developed, which can also be used to minimise the absolute deviation of workloads in a deterministic environment. The experimental results for a set of benchmark problems show that the proposed algorithm outperforms the existing algorithms in terms of solution quality and running time.

Federated integration of networked manufacturing service platforms

Networked manufacturing is an advanced manufacturing pattern that was born of information technologies and suits the networked economic environment. Networked manufacturing service platforms have been widely established to support this new pattern. Since the island problems are retarding further development of networked manufacturing, integration of existing networked manufacturing platforms is in demand. A federated integration mode is proposed to integrate the existing networked manufacturing platforms and provide a large-scale distributed resource sharing and cooperative environment. The nature of federated integration is discussed, and the architecture of federated integration system was put forward along with a set of rules and three types of integration services. Two key issues in federated integration are discussed in detail. One is the federation management, including the hierarchy of federations, the basic states of federations and the state-keeping mechanism using factory/instance pattern. The other issue is the authentication, authorization and access control in across-platform applications. Finally, an implementation is presented.

An automatic method for ontology mapping

Ontology mapping is a precondition to achieve interoperability between agents or services using different ontologies. Today, a series of methods for ontology mapping have been reported. However in the existing literature, the focus has so far been on computing similarity and establishing equal mapping relation. In practice, it is possible to have other mapping relations besides equal mapping, such as subclass mapping relation. In this paper a new method for ontology mapping, FCA-Mapping, is presented. FCA-Mapping is based on Formal Concept Analysis (FCA) theory. By computing relation measures between entities of different ontologies, it can automatically establish equal and subclass mapping relations.

Ontology Fusion in High-Level-Architecture-Based Collaborative Engineering Environments

In high-level-architecture (HLA)-based distributed heterogeneous collaborative engineering environments (CEEs), the construction of federation object model files is time consuming. This paper presents an ontology fusion approach aiming at establishing a common understanding in such collaborative environments. The proposed approach has three steps: ontology mapping, ontology alignment, and ontology merging. Ontology mapping employs a top-down approach to explore all bridge relations between two terms from different ontologies based on bridge axioms and deduction rules. Ontology alignment adopts a bottom-up approach to discover implicit bridge relations between two terms from different domain ontologies based on equivalent inference. Ontology merging generates a new collaboration ontology from discovered equivalent bridge relations. It adopts an axiom-based ontology fusion strategy and takes heavy-weighted ontologies into consideration. It can find all the explicit and derived interontology relations. In a typical CEE, the proposed approach has a great potential to improve the efficiency of preparation for HLA-based collaborative engineering processes, reduce the work load for adaptive adjustment of existing platforms, and enhance the reusability and flexibility of CEEs. A case study has been conducted to validate the feasibility of the proposed approach.

Petri Net and GASA Based Approach for Dynamic JSP

A Petri net with controller is used to model discrete events in flexible job shop scheduling with results obtained based on genetic algorithm and simulated annealing algorithm. In order to assure the stability of manufacture, and the job shop production ability can be maintained farthest, a new classified scheduling method is presented to the job shop scheduling problem (JSP) with dual-resource constraints and multiple disturbances. Firstly, classified based on machine repairing time, and worker leaving time, and task of order cancelling; and then deciding whether it is rescheduled based on remainder task after machine repairing and labor returning. When urgent order comes, remainder jobs and urgent jobs are disposed separately, and then making integration, and through finding optimal results of remainder jobs based on urgent jobs result is optimal, and the whole and local optimal results can be found through this method. Scheduling examples show that the method is available and efficient.

Multidisciplinary Collaboration Simulation Optimization Platform for complex product design

Complex products are integrated by many different kinds of subsystems through complex couplings. Most subsystems come from many different disciplinary such as mechanic system, control system, aerodynamic system and etc.. In order to study the behavior of Complex product, Multidisciplinary collaboration simulation is established by High Level Architecture (HLA). In order to get the best solution, collaboration optimization (CO) platform has been proposed to improve the performance of complex product. This paper proposed a collaboration simulation optimization platform to integrate the function of HLA based collaboration simulation and CO platform. The platform includes disciplinary modeling and simulation module, MDO functional module and HLA/RTI architecture. It can improve the design efficiency and reduce the cost of complex product design.

A Prototype Architecture for Assembly-Oriented Cyber-Physical Systems

ACPS is a new generation intelligent system based on the embedded systems, sensing technology and networked connectivity. As a typical application of CPS, it has many special features different from the traditional systems. According to these features, a four-layer architecture is proposed which consists of Physical Layer, Network Layer, Co-processing Layer and Application Layer. Furthermore, some research directions and challenges of ACPSs are suggested, and the ultimate goal is to develop foundations and techniques for building safe and effective ACPSs.

Ontology fusion in HLA-based collaborative product development

This paper presents a novel ontology fusion approach which aims to establish a mutual understanding among HLA (High Level Architecture) -based distributed heterogeneous collaborative product development systems. The approach includes three steps: ontology mapping, ontology alignment and ontology merging. It adopts an axiom-based deduction ontology fusion strategy, and takes heavy weighted ontologies into consideration. It can find all the explicit and derived inter-ontology relations, and furthermore it reaches the active upper bounds of implicit equivalent inter-ontology relations searching. The proposed approach has great potential to improve the efficiency of preparation for HLA-based collaborative product development, reduce the work load for adaptive adjustment of ever-existing platforms, and enhance the applicability and flexibility of collaborative development systems.

A model of the expanded grey theory

It was a great process to develop from Cantor sets theory to fuzzy theory and grey theory. Based on the process, the author analyzed the essence of grey as viewed from philosophy-mathematics field. Then the grey theory was expanded to higher orders and a hierarchical description was given out. In the description, there existed two indexes (degree of greyness and degree of fuzziness). Finally, based on it, the author bought forward three useful simplified model-building methods. These methods can be added into many advanced methods, such as artificial neural networks and genetic algorithms.