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The paper discusses a novel geometric reasoning method that supports the definition of assembly sequence planning models departing from the CAD models of the parts involved. Specifically, by means of the presented algorithms that use a so-called collision point cloud approach one can determine the precise disassembly directions of parts having complex polygon mesh models. This information can be applied when defining assembly planning models both for suggesting precedence constraints as well as parameters for assembly operations. The presented heuristic algorithm was able to overcome certain shortcomings of earlier methods working with polygon mesh representations, and proved to be successful both in handling abstract and real-life industrial use cases. Working examples from both categories are presented in the paper. [ABSTRACT FROM AUTHOR]

The paper presents a generic workflow of semi-automated and optimized process planning in mechanical assembly. It supports the production engineer throughout the entire planning process, departing from part analysis via task sequencing up to the generation of detailed work instructions. Main stages such as part analysis, macro planning and various aspects of micro planning are presented along with a feedback mechanism which warrants executability of plans using the available technological and human resources. Emphasis is set on the essential role of geometric reasoning and its combined use with constrained optimization. The workflow is demonstrated on industrial case studies. [ABSTRACT FROM AUTHOR]

The production industry is moving towards the next generation of assembly, which is conducted based on safe and reliable robots working in the same workplace alongside with humans. Focusing on assembly tasks, this paper presents a review of human–robot collaboration research and its classification works. Aside from defining key terms and relations, the paper also proposes means of describing human–robot collaboration that can be relied on during detailed elaboration of solutions. A human–robot collaborative assembly system is developed with a novel and comprehensive structure, and a case study is presented to validate the proposed framework. [ABSTRACT FROM AUTHOR]

The paper proposes a generic approach to assembly planning where individual tasks, with detailed technological content specified by features, must be combined into an optimal assembly plan subject to technological and geometric constraints. To cope with the complexity and variety of the constraints that refer to the overall assembly process, Benders decomposition is applied. The macro-level master problem looks for the optimal sequencing and resource assignment of the tasks, while sub-problem modules ensure plan feasibility on the micro-level from aspects of technology, fixturing, tooling, and collision. Constraints are also dynamically generated for the master problem. The approach is demonstrated in automotive assembly. [ABSTRACT FROM AUTHOR]

Remote laser welding (RLW) has received increased attention in the recent years due to its benefits in terms of processing speed, lower investment, cost per stitch, and process flexibility. However, its potential in automotive assembly remains under exploited, mainly due to challenges involving system, process and fixture design, and part variation challenges. In this paper, an integrated rapid deployment framework for RLW process is proposed to improve ‘ right-first-time ’ implementation of RLW in assembly systems. It enables closed-loop optimization of system layout, task assignment, fixture layout, process parameters, robot path planning and programming as an interlinked iterative approach. The results are demonstrated in an automotive door assembly pilot study. [ABSTRACT FROM AUTHOR]