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Owing to the numerous part models and massive datasets used in automobile assembly design, virtual assembly software cannot simulate a whole vehicle smoothly in real time. For this reason, implementing a new virtual assembly environment for massive complex datasets would be a significant achievement. The paper aims to focus on this problem.

A new system named “Grid‐enabled collaborative virtual assembly environment” (GCVAE) is proposed in the paper, and it comprises three parts: a private grid‐based support platform running on an inner network of enterprise; a service‐based parallel rendering framework with a sort‐last structure; and a multi‐user collaborative virtual assembly environment. These components would aggregate the idle resources in an enterprise to support assembly simulation with a large complex scene of whole vehicle.

The system prototype proposed in the paper has been implemented. The following simulations show that it can support a complex scene in a real‐time mode by using existing hardware and software, and can promote the efficient usage of enterprise resources.

Using the GCVAE, it is possible to aggregate the idle resources in an enterprise to run assembly simulations of a whole automobile with massively complex scenes, thus observably reducing fault occurrence rates in future manufacturing.

The paper introduces a new grid‐enabled methodology into research on collaborative virtual assembly system which can make the best use of idle resources in the enterprise to support assembly simulations with massively complex product models. A video‐stream‐based method was used to implement the system; this enables designers to participate ubiquitously in the simulation to evaluate the assembly of the whole automobile without hardware limitations.

In the current era of Industry 4.0, the manufacturing industries are striving toward mass production with mass customization by considering human–robot collaboration. This study aims to propose the reconfiguration of assembly systems by incorporating multiple humans with robots using a human–robot task allocation (HRTA) to enhance productivity.

A human–robot task scheduling approach has been developed by considering task suitability, resource availability and resource selection through multicriteria optimization using the Linear Regression with Optimal Point and Minimum Distance Calculation algorithm. Using line-balancing techniques, the approach estimates the optimum number of resources required for assembly tasks operating by minimum idle time.

The task allocation schedule for a case study involving a punching press was solved using human–robot collaboration, and the approach incorporated the optimum number of appropriate resources to handle different types of proportion of resources.

This proposed work integrates the task allocation by human–robot collaboration and decrease the idle time of resource by integrating optimum number of resources.

Presents an integrated approach to assembly planning for manufacturing printed circuit boards (PCBs). The integrated manufacturing assembly planning system (IMAPS) is a system that incorporates knowledge‐based techniques to assist process engineers with the development of assembly plans for building PCBs. IMAPS has been developed in a two‐year project with a multinational telecommunications manufacturer and the Alberta Research Council of Canada. The scope of IMAPS is to develop an integrated environment that takes full advantage of electronic information for assembly planning of PCBs. Several functions in the company can be integrated with IMAPS, including product design, detailed assembly planning, line balancing and generation of shop floor drawings. Information stored in the manufacturing and design databases of the corporation, about a PCB to be assembled, is employed by a knowledge‐based module to generate assembly plans to build the PCB. A line balancing procedure is employed to select the most adequate assembly plan of those generated by the knowledge‐based module. The final assembly plan is then presented to the operators as a diagram with instructions for the assembly of the PCB. IMAPS has increased the speed to generate assembly plans from 120 hours to four hours. The final computer‐aided assembly planning system implemented in the company has taken the concepts developed in IMAPS; they have been implemented in C and C++. Lessons and experiences learned while developing and implementing IMAPS are presented.

In response to the station design and flexible resources allocation of the aircraft moving assembly line, a new problem named flexible resource investment problem based on project splitting (FRIP_PS), which minimizes total cost of resources with a given deadline are proposed in this paper.

First, a corresponding mathematical model considering project splitting is constructed, which needs to be simultaneously determined together with job scheduling to acquire the optimized project scheduling scheme and resource configurations. Then, an integrated nested optimization algorithm including project splitting policy and job scheduling policy is designed in this paper. In the first stage of the algorithm, a heuristic algorithm designed to get the project splitting scheme and then in the second stage a genetic algorithm with local prospective scheduling strategy is adopted to solve the flexible resource investment problem.

The heuristic algorithm of project splitting gets better project splitting results through the job shift selection strategy and meanwhile guides the algorithm of the second stage. Furthermore, the genetic algorithm solves resources allocation and job schedule through evaluation rules which can effectively solve the delayed execution of jobs because of improper allocation of flexible resources.

This paper represents a new extension of the resource investment problem based on aircraft moving assembly line. An effective integrated nested optimization algorithm is proposed to specify station splitting scheme, job scheduling scheme and resources allocation in the assembly lines, which is significant for practical engineering applications.

Resource-constrained assembly lines are widely found in industries that manufacture complex products. In such lines, tasks may require specific resources to be processed. Therefore, decisions on which tasks and resources will be assigned to each station must be made. When the number of available stations is fixed, the problem’s main goal becomes the minimisation of cycle time (type-II version). This paper aims to explore this variant of the problem that lacks investigation in the literature.

In this paper, the authors propose mixed-integer linear programming (MILP) models to minimise cycle time in resource-constrained assembly lines, given a limited number of stations and resources. Dedicated and alternative resource types for tasks are considered in different scenarios.

Besides, past modelling decisions and assumptions are questioned. The authors discuss how they were leading to suboptimal solutions and offer a rectification.

The proposed models and data set fulfil more practical concerns by taking into account characteristics found in real-world assembly lines.

The proposed MILP models are applied to an existing data set, results are compared against a constraint programming model, and new optimal solutions are obtained. Moreover, a data set extension is proposed due to the simplicity of the current one and instances up to 70 tasks are optimally solved.

The purpose of this paper is to provide a knowledge-enabled digital twin for smart design (KDT-SD) of aircraft assembly line (AAL) to enhance the AAL efficiency, performance and visibility. Modern AALs usually need to have capabilities such as digital-physical interaction and self-evaluation that brings significant challenges to traditional design method for AAL. The digital twin (DT) combining with reusable knowledge, as the key technologies in this framework, is introduced to promote the design process by configuring, understanding and evaluating design scheme.

The proposed KDT-SD framework is designed with the introduction of DT and knowledge. First, dynamic design knowledge library (DDK-Lib) is established which could support the various activities of DT in the entire design process. Then, the knowledge-driven digital AAL modeling method is proposed. At last, knowledge-based smart evaluation is used to understand and identify the design flaws, which could further improvement of the design scheme.

By means of the KDT-SD framework proposed, it is possible to apply DT to reduce the complexity and discover design flaws in AAL design. Moreover, the knowledge equips DT with the capacities of rapid modeling and smart evaluation that improve design efficiency and quality.

The proposed KDT-SD framework can provide efficient design of AAL and evaluate the design performance in advance so that the feasibility of design scheme can be improved as much as possible.

The purpose of this paper is to describe a comprehensive modelling technique that supports the assembly of very complex products that require intensive use of both computerized worker guidance and automation. The modelling enables the planning of this complex process.

The proposed approach utilizes and extends typical product documentation (such as route cards and bill of materials (BOM)) to form hierarchical Petri net in a stepwise process. The suggested framework models the dynamic progress of the assembly process, and can generate route card instructions for manual operations, or ladder diagrams (LDs) for automation.

The model can help the generation of computerized control over route cards for manual assembly operations. For automated processes, the translation algorithm of the model to LD enables its application on currently available equipment (programmable logic controllers (PLCs)).

The proposed framework heavily depends on the BOM data quality. So it is crucial to verify that the BOM data is not ill-defined before applying the proposed framework. Future research could report on the implementation of this model in assembly processes, or suggest another modelling technique.

The model enables the integration of computer control over both manual and automated assembly processes. This enables seamless transition between these two very different operations. This ability carries the promise of reducing the cost of code generation and maintenance, and contributes to the progress towards more flexible automation.

This paper presents a new comprehensive modelling technique that may support planning, simulating, tracing, and controlling the assembly process. The technique for the first time integrates modelling of both manual and automated assembly operation.

This paper sets out to integrate research on knowledge management with the dynamic capabilities approach. This paper will add to the understanding of dynamic capabilities by demonstrating that dynamic capabilities can be seen as composed of concrete and well‐known knowledge management activities.

This paper is based on a literature review focusing on key knowledge management processes and activities as well as the concept of dynamic capabilities, the paper connects these two approaches. The analysis is centered on knowledge management activities which then are compiled into dynamic capabilities.

In the paper eight knowledge management activities are identified; knowledge creation, acquisition, capture, assembly, sharing, integration, leverage, and exploitation. These activities are assembled into the three dynamic capabilities of knowledge development, knowledge (re)combination, and knowledge use. The dynamic capabilities and the associated knowledge management activities create flows to and from the firm's stock of knowledge and they support the creation and use of organizational capabilities.

The findings in the paper demonstrate that the somewhat elusive concept of dynamic capabilities can be untangled through the use of knowledge management activities. Practicing managers struggling with the operationalization of dynamic capabilities should instead focus on the contributing knowledge management activities in order to operationalize and utilize the concept of dynamic capabilities.

The paper demonstrates that the existing research on knowledge management can be a key contributor to increasing our understanding of dynamic capabilities. This finding is valuable for both researchers and practitioners.

Environmental problems in manufacturing industries are a global issue owing to severe lack fossil resources. In assembly sequence planning (ASP), the research effort mainly aims to improve profit and human-related factors, but it still lacks in the consideration of the environmental issue. This paper aims to present an energy-efficient model for the ASP problem.

The proposed model considered energy utilization during the assembly process, particularly idle energy utilization. The problem was then optimized using moth flame optimization (MFO) and compared with well-established algorithms such as genetic algorithm (GA), particle swarm optimization (PSO) and ant colony optimization (ACO). A computational test was conducted using five assembly problems ranging from 12 to 40 components.

The results of the computational experiments indicated that the proposed model was capable of generating an energy-efficient assembly sequence. At the same time, the results also showed that MFO consistently performed better in terms of the best and mean fitness, with acceptable computational time.

This paper proposed a new energy-efficient ASP model that can be a guideline to design assembly station. Furthermore, this is the first attempt to implement MFO for the ASP problem.

Merges the latest results obtained by the holonic manufacturing systems (HMS) consortium with the latest developed standards for platform interoperability released by the Foundation for Intelligent Physical Agents (FIPA) to propose a novel e‐business model: the holonic e‐enterprise (HE). The HE extends both the HMS and FIPA models. On one side it extends the holonic manufacturing paradigm with one top level, the inter‐enterprise one. On the other side it extends the multi‐agent system (MAS) paradigm to the hardware (physical machine) level.