PurposeThe proposed method is to generate the 3 D model of frame assemblies based on their topological model automatedly. It was a very demanding task and there was no appropriate automated method to facilitate this work.Design/methodology/approachThe proposed method includes two stages. The first stage is decisive. In this stage, a deep learning network and the Chu–Liu–Edmonds algorithm are used to recognize contact relations among parts. Based on this recognition, the authors perform a geometrical computation in the second stage to finalize the 3 D model.FindingsThe authors verify the feasibility of the proposed method using a case study and find that the classification rate of the deep learning network for part contact relations is higher than 75 per cent. Furthermore, more accurate results could be achieved with modification by the Chu–Liu–Edmonds algorithm. The proposed method has lower computational complexity compared with traditional heuristic methods, and its results are more consistent with existing designs.Research limitations/implicationsThe paper introduces machine learning method into assembly modelling issue. The proposed method divides the assembly modelling into two steps and solves the assemble relation creatively.Practical implicationsFrame assemblies are fundamental to many areas. The proposed method could automate frame assembly modelling in a viable way. It could benefit design and manufacture process significantly.Originality/valueThe proposed method expands the application of machine learning into a new field. It would be more useful than simple machine learning in industry. The proposed method is better than general heuristic algorithms. It outputs identical results when the inputs are the same. Meanwhile, the algorithmic complexity in worst situation is better than general heuristic algorithms.

Purpose Manufacturing errors, which will propagate along the assembly process, are inevitable and difficult to analyze for complex products, such as aircraft. To realize the goal of precise assembly for an aircraft, with revealing the nonlinear transfer mechanism of assembly error, a set of analytical methods with response to the assembly error propagation process are developed. The purpose of this study is to solve the error problems by modeling and constructing the coordination dimension chain to control the consistency of accumulated assembly errors for different assemblies. Design/methodology/approach First, with the modeling of basic error sources, mutual interaction relationship of matting error and deformation error is analyzed, and influence matrix is formed. Second, by defining coordination datum transformation process, practical establishing error of assembly coordinate system is studied, and the position of assembly features is modified with actual relocation error considering datum changing. Third, considering the progressive assembly process, error propagation for a single assembly station and multi assembly stations is precisely modeled to gain coordination error chain for different assemblies, and the final coordination error is optimized by controlling the direction and value of accumulated error range. Findings Based on the proposed methodology, coordination error chain, which has a direct influence on the property of stealthy and reliability for modern aircrafts, is successfully constructed for the assembly work of the jointing between leading edge flap component and wing component at different assembly stations. Originality/value Precise assembly work at different assembly stations is completed to verify methodology’s feasibility. With analyzing the main comprised error items and some optimized solutions, benefit results for the practical engineering application showing that the maximum value of the practical flush of the profiles between the two components is only 0.681 mm, the minimum value is only 0.021 mm, and the average flush of the entire wing component is 0.358 mm, which are in accordance with theoretical calculation results and can successfully fit the assembly requirement. The potential user can be the engineers for manufacturing the complex products.

PurposeThis paper aims to propose a conceptual scale model of mobile drilling robot according to the actual drilling rig and working conditions to improve the safety and automation of drilling in tunnel construction and coal mining applications.Design/methodology/approachA couple of pinion and rack serves as the support mechanism driven by a motor with low rotation speed at high power, and these components are assembled in the center of the robot to tightly fasten the whole body together. The drilling rod and the sleeve are connected through a hole with screw thread so that the rod feeds and rotates simultaneously along with the sleeve. The robot model is automatically controlled by a single-chip microcomputer, and the anti-disturbance circuit is designed as well. A five-step rule obstacle avoidance method is proposed to ensure safe and reliable movement.FindingsThe results of simulation experiments on drilling operation do indicate that the mechanism and control method are feasible and effective.Research limitations/implicationsThe robot is nearly complete but indeed remains only an experimental machine.Originality/valueThe design of the mechanism structure for the conceptual robot is novelty. The method of five-step rule obstacle avoidance can improve reliability of obstacle avoidance according to the experimental results, which can meet the requirements of complex working conditions underground coal mine.

PurposeLarge supermarkets, chain stores and enterprises with large-scale warehousing put forward higher standards and requirements for the automation and informatization of warehouses. As one of the fast-growing commercial supermarkets in China, the traditional warehouse management mode has restricted the rapid development of Yonghui Superstores to a certain extent. The purpose of this paper is to find out how the existing warehouse mode can be changed and to solve the existing problems of warehouse management of Yonghui Superstores.Design/methodology/approachThis research puts forward construction of warehouse center, which is based on radio frequency identification (RFID) and sensor technology, then designs the model for receiving, storage, operations management, distribution and outbound to solve the existing problems of warehouse management of Yonghui Superstores.FindingsWhat technologies should be adopted to meet storage requirements? How to monitor the storage environment in real time and improve the operation and management level of the warehouse? This study found that building a warehouse center based on RFID and sensor technology was a good solution.Research limitations/implicationsThe Yonghui Superstores warehouse center model lacks corresponding simulation experiments, and the investment and income are difficult to estimate quantitatively.Practical implicationsThis paper has designed and discussed the warehouse center model based on RFID and sensor technology, which provides a few references for the actual investment and construction of a warehouse center. In addition, the warehouse center model has strong generalized applicability and could be widely used in various enterprises.Social implicationsThe warehouse center could improve the warehouse management level of Yonghui Superstores and change the traditional warehouse management mode. To some extent, it improves the enterprise flexibility of the market, which will be of great significance to improve business efficiency and enhance brand image and competitiveness.Originality/valueThis study takes Yonghui Superstores as a case to analyze the problems of warehousing management in detail and then designs a warehouse center based on RFID and sensor technology. The study discusses the location and distribution, software and hardware selection, benefits evaluation, significances and return on investment, which makes the warehouse center model versatile, technically feasible and economically applicable.

Purpose This paper is concerned with the repetitive trajectory tracking control for space manipulators under model uncertainties and vibration disturbances. Design/methodology/approach The model uncertainties and link vibration of manipulators will degrade the tracking performance of space manipulators; in this paper, a new hybrid control scheme that consists of a composite hierarchical anti-disturbance controller and an iterative learning controller is developed to solve this problem. Findings The composite hierarchical controller can effectively attenuate model uncertainties and reject vibration disturbances, whereas the iterative learning controller is able to improve the tracking accuracy for repetitive reference trajectory. Originality/value The proposed scheme compensates for the shortcomings of iterative learning control which can only deal with repetitive disturbances, ensuring the accuracy and repeatability of space manipulators under model uncertainties and random disturbances.

PurposeDeterminative locating and riveting distortions are highly coupled at assembly locale. Recent methods only take every tested or assumed locating errors at the mating surface into the process planning for the assemblies in a simple form. However, the growth of part number makes it nearly infeasible to take every locating error at every mating surface into the dimensional precision calculation. This paper aims to provide a solid riveting process planning for the reduction of practical locating-related distortions.Design/methodology/approachLarge-scale metrology firstly measures the determinative coordinates for the locating-deviated key points. Iterative finite element (FE) analyses then calculate the riveting-related key point distortions from every rivet upsetting directions (UDs) and assembly sequence. These key points on the actual assembly contour and relative FE nodes yield two virtual planes. Virtual plane manipulation adds the riveting distortions into the locating-deviated coordinates. Finally, optimal algorithm integrates the iterative FE analyses with virtual plane manipulation.FindingsCase studies validate that the virtual plane manipulation coincides with the test well, and the proposed method has good compensation of practical locating distortion.Research limitations/implicationsThe optimized rivet UDs may be set in a chaotic distribution, which may complicate the abundant riveting operations and the assembly appearance. Therefore, the use of automatic riveting systems can overcome the operational complexity, and the industrial design of rivet UD distribution will improve the assembly appearance.Practical implicationsThe optimized UDs and assembly sequence are for assembly workers or automatic riveting systems.Originality/valueThe proposed method is the first to reduce the determinative locating distortion by a novel and efficient solid riveting process planning in detail, and the solid riveting process designed is conservative and accurate for practice.

PurposeMulti-robots simultaneously coverage and tracking (SCAT) is the problem of simultaneously covering area and tracking targets, which is essential for many applications, such as delivery service, environment monitor, traffic surveillance, crime monitor, anti-terrorist mission and so on. The purpose of this paper is to improve the performance of detected target quantity, coverage rate and less deadweight loss by designing a self-organized method for multi-robots SCAT.Design/methodology/approachA self-organized reciprocal control method is proposed, coupling task assignment, tracking and covering, equipped with collision-avoiding ability naturally. First, SCAT problem is directly modeled as optimal reciprocal coverage velocity (ORCV) in velocity space. Second, the preferred velocity is generated by calculating the best velocity to the center of some robot detected targets. ORCV is given by adjusting the velocity relative to neighbor robots’ toward in optimal coverage velocity (OCV); it is proven that OCV is collision-free assembly. Third, some corresponding algorithms are designed for finding optimal velocity under two situations, such as no detected targets and empty ORCV.FindingsThe simulation results of two cases for security robots show that the proposed method has detected more targets with less deadweight loss and decision time and no collisions anytime.Originality/valueIn this paper, a self-organized reciprocal control method is proposed for multi-robots SCAT problem, which is modeled in velocity space directly, different to the traditional method modeling in configuration space. What is more, this method considers the reciprocal of robots that contributes to the better accomplishment of SCAT cooperatively.

PurposeAssembly sequence optimization is a difficult combinatorial optimization problem having to simultaneously satisfy various feasibility constraints and optimization criteria. Applications of evolutionary algorithms have shown a lot of promise in terms of lower computational cost and time. But there remain challenges like achieving global optimum in least number of iterations with fast convergence speed, robustness/consistency in finding global optimum, etc. With the above challenges in mind, this study aims to propose an improved flower pollination algorithm (FPA) and hybrid genetic algorithm (GA)-FPA.Design/methodology/approachIn view of slower convergence rate and more computational time required by the previous discrete FPA, this paper presents an improved hybrid FPA with different representation scheme, initial population generation strategy and modifications in local and global pollination rules. Different optimization objectives are considered like direction changes, tool changes, assembly stability, base component location and feasibility. The parameter settings of hybrid GA-FPA are also discussed.FindingsThe results, when compared with previous discrete FPA and GA, memetic algorithm (MA), harmony search and improved FPA (IFPA), the proposed hybrid GA-FPA gives promising results with respect to higher global best fitness and higher average fitness, faster convergence (especially from the previously developed variant of FPA) and most importantly improved robustness/consistency in generating global optimum solutions.Practical implicationsIt is anticipated that using the proposed approach, assembly sequence planning can be accomplished efficiently and consistently with reduced lead time for process planning, making it cost-effective for industrial applications.Originality/valueDifferent representation schemes, initial population generation strategy and modifications in local and global pollination rules are introduced in the IFPA. Moreover, hybridization with GA is proposed to improve convergence speed and robustness/consistency in finding globally optimal solutions.

PurposeThe purpose of this paper is to propose an adaptive control for a redundant robot manipulator interacting physically with the environment, especially with the existence of humans, on its body.Design/methodology/approachThe redundant properties of the robot manipulator are used and a reference velocity variable is introduced to unify the operation-space tracking control and the null-space impedance control under one common framework. Neural networks are constructed to deal with unstructured and unmodeled dynamic nonlinearities. Lyapunov function is used during the course of control design and simulation studies are carried out to further illustrate the effectiveness of the proposed strategies.FindingsSatisfying tracking performance in the operation-space and compliance behavior in the null-space of the redundant robot manipulator are ensured simultaneously.Originality/valueThe design procedure of redundant robot manipulators control can be greatly simplified, and the framework of multi-priority control can be transformed into a joint-space velocity tracking problem via the introducing of a reference velocity variable.

PurposeThis research aims to address the cost-oriented stochastic assembly line balancing problem (ALBP) and propose a chance-constrained programming model.Design/methodology/approachThe cost-oriented stochastic ALBP is solved for small- to medium-sized problems. Owing to the non-deterministic polynomial-time (NP)-hardness problem, a multiple rule-based genetic algorithm (GA) is proposed for large-scale problems.FindingsThe experimental results show that the proposed GA has superior performance and efficiency compared to the global optimum solutions obtained by the IBM ILOG CPLEX optimization software.Originality/valueTo the best of the authors’ knowledge, only one study has discussed the cost-oriented stochastic ALBP using the new concept of cost. Owing to the NP-hard nature of the problem, it was necessary to develop a heuristic or meta-heuristic algorithm for large data sets; this research paper contributes to filling this gap.