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The purpose of this paper is to report on a geometrical integration methodology that can be used to organise some types of these systems. Most multipath delivery systems, such as Building Services (BSs), are arbitrarily distributed with no known solution to reduce the complexity in the way channels are arranged.

Integration for optimal functionality through reduction of geometrical complexity is achieved by understanding the elements of complexity within current practices; identifying commonalities between the various components which can be used for integration; performing an axiomatic design to resolve design complications; adopting theory of inventive problem-solving for methodology and process development towards optimal functionality; and generating a mathematical solution to inform digital modelling of optimal design. The study takes into account thermophysical and electromagnetic interactions between utilities and uses novel mathematical manipulations based on designing a manifold of spherical and cylindrical geometries joined using Bezier surfaces.

Once a solution was reached, computer-aided design (CAD) iterations were undertaken for channelling six BSs into a single unit. The outcome was concentric cylindrical–spherical shells superimposed with spacings of typically few millimetres to deliver/distribute the utilities. It is applied to bring together BSs into a single trunking system at minimal, yet appropriate, proximal distances, and it allows distribution of any number of services in any direction. Physical prototypes were produced and initial testing of their performance (reported elsewhere) has been encouraging.

A design methodology for integrating arbitrary distributed paths/conduits. The approach could be incorporated into CAD tools as a design feature to facilitate integration of multipath delivery systems.

Agreements IMF‐ICorrST The President and Council of the Institute of Metal Finishing are pleased to announce that an agreement has been made with the Institution of Corrosion Science and Technology whereby the IMF will supply administrative services to ICorrST from Exeter House with effect from the 1st January, 1983.

To design a flexible integrated robotic assembly and rework (remanufacturing) cell for assembly, selective assembly and rework of advanced surface mount components (SMCs) using the generic methodology developed in this paper.

Manual rework procedures are investigated for all advanced SMCs. General and specific component‐related rework considerations are obtained and necessary tooling candidates for automation are determined. This is followed by determination of the specific automated rework procedure and selection of suitable tooling for automated robotic rework and generation and evaluation of design concepts.

The developed methodology, which considers the reflow tool at the centre of the development process, has worked well in designing a flexible integrated robotic assembly and rework cell.

This study identified the rework requirements for advanced SMCs, the essential features for rework reflow tools, criteria for comparing reflow tools, and a generic procedure for design and concept selection.

It provides valuable knowledge for designers of flexible integrated robotic assembly and rework cells for assembly, selective assembly and rework of advanced SMCs.

The purpose of this paper is to perform a comparative assessment on working of the existed subassembly identification (SI) methods, which are widely practiced during the product development stage and to propose an improved method for solving the SI problem in assembly sequence planning (ASP).

The cut-set method is found as a suitable method among various knowledge-based methods such as the theory of loops, theory of connectors and theory of clusters for the workability enhancement to meet the current requirements. Necessary product information is represented in the matrix format by replacing the traditional AND/OR graphs and the advanced predicates are included in the evaluation criteria.

The prominent methods in SI are followed a few of the predicates to avoid complexity in solution generation. The predicate consideration is found as the most influencing factor in eliminating the infeasible part combinations at SI. However, the quality of identified subassemblies without advanced predicates is not influencing the solution generation phase but practical applicability is affecting adversely.

The capability of performing SI by the cut-set method is improved to deal with the complex assembly configurations. The improved method is tested by applying on different assembly configurations and the effectiveness is compared with other existent methods of ASP along with the conventional method.

As complex analysis of contact models is required in the traditional assembly strategy, it is still a challenge for a robot to complete the multiple peg-in-hole assembly tasks autonomously. This paper aims to enable the robot to complete the assembly tasks autonomously and more efficiently, with the strategies learned by reinforcement learning (RL), a learning-accelerated deep deterministic policy gradient (LADDPG) algorithm is proposed.

The multiple peg-in-hole assembly strategy is designed in two modules: an advanced planning module and a bottom control module. The advanced module is completed by the LADDPG agent, which is used to derive advanced commands based on geometric and environmental constraints, that is, the desired contact force. The bottom-level control module will drive the robot to complete the compliant assembly task through the adaptive impedance algorithm according to the command set issued by the advanced module. In addition, a set of safety assurance mechanisms is developed to safely train a collaborative robot to complete autonomous learning.

The method can complete the assembly tasks well through RL, and it can realize satisfactory compliance of the robot to the environment. Compared with the original DDPG algorithm, the average values of the instantaneous maximum contact force and contact torque during the assembly process are reduced by approximately 38% and 74%, respectively.

The entire algorithm can also be applied to other robots and the assembly strategy can be applied in the field of the automatic assembly.

A compliant assembly strategy based on the LADDPG algorithm is proposed to complete the automated multiple peg-in-hole assembly tasks.

The purpose of this paper is to develop a modeling and interactive operating method for virtual assembly (VA) to support assembly process generation based on interactive operation.

This paper puts forward an assembly semantic modeling method for interactive assembly and process generation after the analysis on requirements of operation process generation. Based on this semantic model, methods for semantic generation, semantic processing and assembly motion extraction from interactive operation are presented. Partial process generation of auto engine is proposed to verify the approaches in this paper.

The application shows that assembly semantic modeling and operating methods can support process generation based on VA operations.

The approaches presented in this paper improve the efficiency of assembly process, making assembly process intuitive and natural.

This paper aims to provide a shimming method based on scanned data and finite element analysis (FEA) for a wing box assembly involving non-uniform gaps. The effort of the present work is to deal with gap compensation problem using hybrid shims composed of solid and liquid forms.

First, the assembly gaps of the mating components are calculated based on the scanned surfaces. The local gap region is extracted by the seed point and region growth algorithm from the scattered point cloud. Second, with the constraints of hole margin, gap space and shim specification, the optional shimming schemes are designed by the exhaustive searching method. Finally, the three-dimensional model of the real component is reconstructed based on the reverse engineering techniques, such as section lines and sweeping. Using FEA software ABAQUS, the stress distribution and damage status of the joints under tensile load are obtained for optimal scheme selection.

With the scanned mating surfaces, the non-uniform gaps are digitally evaluated with accurate measurement and good visualization. By filling the hybrid shims in the assembly gaps, the joint structures possess similar load capacity but stronger initial stiffness compared to the custom-shimmed structures.

This method has been tested with the interface data of a wing tip, and the results have shown good efficiency and automation of the shimming process.

The proposed method can decrease the manufacturing cost of shims, shorten the shimming process cycle and improve the assembly efficiency.

The product family assembly line (PFAL) is a mixed model-assembly line, which is widely used in mass customization and intelligent manufacturing. The purpose of this paper is to study the problem of PFAL, a flexible (evolution) planning method to respond to product evolution for PFAL, to focus on product data analysis and evolution planning method.

The evolution balancing model for PFAL is established and an improved NSGA_II (INSGA_II) is proposed. From the perspective of data analysis, dynamic characteristics of PFAL are researched and analyzed. Especially the tasks, which stability is considered, can be divided into a platform and individual task. In INSGA_II algorithm, a new density selection and a decoding method based on sorting algorithms are proposed to compensate for the lack of traditional algorithms.

The effectiveness and feasibility of the method are validated by an example of PFAL evolution planning for a family of similar mechanical products. The optimized efficiency is significantly improved using INSGA_II proposed in this paper and the evolution planning model proposed has a stronger ability to respond to product evolution, which maximizes business performance over an effective period of time.

The assembly line designers and managers in discrete manufacturing companies can obtain an optimal solution for PFAL planning through the evolution planning model and INSGA-II proposed in this paper. Then, this planning model and optimization method have been successfully applied in the production of small wheel loaders.

The purpose of this paper is to propose a novel method under the name of genetic simulated annealing algorithm (GSAA) and ant colony optimization (ACO) algorithm for assembly sequence planning (ASP) which is possessed of the competence for assisting the planner in generating a satisfied and effective assembly sequence with respect to large constraint assembly perplexity.

Based on the genetic algorithm (GA), simulated annealing, and ACO algorithm, the GSAA are put forward. A case study is presented to validate the proposed method.

This GSAA has better optimization performance and robustness. The degree of dependence on the initial assembly sequence about GSAA is decreased. The optimization assembly sequence still can be obtained even if the assembly sequences of initial population are infeasible. By combining GA and simulated annealing (SA), the efficiency of searching and the quality of solution of GSAA is improved. As for the presented ACO algorithm, the searching speed is further increased.

Traditionally, GA heavily depends on the choosing original sequence, which can result in early convergence in iterative operation, lower searching efficiency in evolutionary process, and non‐optimization of final result for global variable. Similarly, SA algorithms may generate a great deal of infeasible solutions in the evolution process by generating new sequences through exchanging position of the randomly selected two parts, which results in inefficiency of the solution‐searching process. In this paper, the proposed GSAA and ACO algorithm for ASP are possessed of the competence for assisting the planner in generating a satisfied and effective assembly sequence with respect to large constraint assembly perplexity.

Examines the tenth published year of the ITCRR. Runs the whole gamut of textile innovation, research and testing, some of which investigates hitherto untouched aspects. Subjects discussed include cotton fabric processing, asbestos substitutes, textile adjuncts to cardiovascular surgery, wet textile processes, hand evaluation, nanotechnology, thermoplastic composites, robotic ironing, protective clothing (agricultural and industrial), ecological aspects of fibre properties – to name but a few! There would appear to be no limit to the future potential for textile applications.