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This paper presents the influence of beam incidence angle on austenitic stainless steel sheet subjected to a high density laser beam having Gaussian power density distribution. Bead‐on trials are conducted on 3.15 mm thick commercial AISI 304 austenitic stainless steel sheet using a Nd:YAG laser source with a maximum output of 2kW in the continuous wave mode. The effects of beam incident angle on the weld bead geometry are studied using finite element analysis. Experiments are conducted with 600, 1000 and 1400W laser power and 800, 1400 and 2000mm/min welding speed. A three dimensional finite element model is developed for the simulation of non‐linear transient thermal analysis of the weld bead geometry for different beam incident angles using the finite element code ANSYS. The result reveals that by increasing the beam incident angle with constant beam power and welding speed, there is a considerable reduction in the depth of penetration‐to‐width ratio (d/w). Further, it is noticed that the process enters into conduction mode of welding from the keyhole mode of welding as the beam angle is increased beyond 10o. The comparison of the simulation results and the experimental data for weld bead geometry with different beam incident angles show good agreement.

Parallel assembly sequence planning (PASP) reduces the overall assembly effort and time at the product development stage. Methodological difficulties at framework development and computational issues at their implementation made the PASP complex to achieve. This paper aims to propose a novel stability concept for subassembly detection to minimize the complexities in PASP.

In this research, a heuristic method is developed to identify, represent and implement the stability predicate to perform subassembly detection and assembly sequence planning (ASP) at the further stages. Stability is organized into static, dynamic, enriched and no stability between the mating assembly parts. The combination of parts that possesses higher fitness is promoted to formulate the final solution about PASP.

The results obtained by applying the proposed concept on complex configurations revealed that stability predicate plays a dominant role in valid subassembly detection and final sequence generation further.

The value of the presented study lies in the three types of stability conditions and effective integration to existed ASP method. Unlike the existed heuristics in subassembly detection, the proposed concept identifies the parallel subassemblies during ASP.

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.

In the present era of Industry 4.0, the manufacturing automation is moving toward mass production and mass customization through human–robot collaboration. The purpose of this paper is to describe various human–robot collaborative (HRC) techniques and their applicability for various manufacturing methods along with key challenges.

Numerous recent relevant research literature has been analyzed, and various human–robot interaction methods have been identified, and detailed discussions are made on one- and two-way human–robot collaboration.

The challenges in implementing human–robot collaboration for various manufacturing process and the challenges in one- and two-way collaboration between human and robot are found and discussed.

The authors have attempted to classify the HRC techniques and demonstrated the challenges in different modes.

Finite element analysis (FEA) has been carried out utilizing the ANSYS software package to assess the failure of thick and thin‐walled steel cylindrical pressure vessels. A simple experimental stress analysis (ESA) procedure is described to evaluate the stress components on inner and outer surfaces of the vessels under internal pressure from the measured surface strains. The procedure is validated considering the strain values of FEA for the applied pressure as measured quantities and obtained the corresponding stress components considering the stress‐strain data of the material from ESA and compared with those of FEA results. Failure pressure estimates from FEA (based on the global plastic deformation) were found to be in good agreement with test results of thin as well as thick‐walled cylindrical vessels made of ductile steel materials.

The purpose of this paper is to investigate and quantify the impact of product complexity, including architectural complexity, on operator learning, productivity and quality performance in both assembly and disassembly operations. This topic has not been extensively investigated in previous research.

An extensive experimental campaign involving 84 operators was conducted to repeatedly assemble and disassemble six different products of varying complexity to construct productivity and quality learning curves. Data from the experiment were analysed using statistical methods.

The human learning factor of productivity increases superlinearly with the increasing architectural complexity of products, i.e. from centralised to distributed architectures, both in assembly and disassembly, regardless of the level of overall product complexity. On the other hand, the human learning factor of quality performance decreases superlinearly as the architectural complexity of products increases. The intrinsic characteristics of product architecture are the reasons for this difference in learning factor.

The results of the study suggest that considering product complexity, particularly architectural complexity, in the design and planning of manufacturing processes can optimise operator learning, productivity and quality performance, and inform decisions about improving manufacturing operations.

While previous research has focussed on the effects of complexity on process time and defect generation, this study is amongst the first to investigate and quantify the effects of product complexity, including architectural complexity, on operator learning using an extensive experimental campaign.

This study aims to address the challenge of automatic guided vehicle (AGV) scheduling for parcel storage and retrieval in an intelligent warehouse.

This study presents a scheduling solution that aims to minimize the maximum completion time for the AGV scheduling problem in an intelligent warehouse. First, a mixed-integer linear programming model is established, followed by the proposal of a novel genetic algorithm to solve the scheduling problem of multiple AGVs. The improved algorithm includes operations such as the initial population optimization of picking up goods based on the principle of the nearest distance, adaptive crossover operation evolving with iteration, mutation operation of equivalent exchange and an algorithm restart strategy to expand search ability and avoid falling into a local optimal solution. Moreover, the routing rules of AGV are described.

By conducting a series of comparative experiments based on the actual package flow situation of an intelligent warehouse, the results demonstrate that the proposed genetic algorithm in this study outperforms existing algorithms, and can produce better solutions for the AGV scheduling problem.

This paper optimizes the different iterative steps of the genetic algorithm and designs an improved genetic algorithm, which is more suitable for solving the AGV scheduling problem in the warehouse. In addition, a path collision avoidance strategy that matches the algorithm is proposed, making this research more applicable to real-world scheduling environments.

The purpose of this study is to develop an elasto-plastic multi-material shell model by which finite element analysis of laser welded joints is carried out at the interface of the heat-affected zone and base material.

The multi-material shell model is implemented on the simple cantilever and double cantilever welded plates to examine the efficiency of the developed model.

By reducing the computational time approximately 20 times with the developed model, the results obtained in the form of von Mises stress and equivalent plastic strain are found in good agreement as compared with the reference solid model.

The accurate and fast prediction of the stresses and strains in the laser welded joints, and the developed multi-material model is helpful to simulate complex industrial welded structures.

Autonomous robots must be able to understand long-term manipulation tasks described by humans and perform task analysis and planning based on the current environment in a variety of scenes, such as daily manipulation and industrial assembly. However, both classical task and motion planning algorithms and single data-driven learning planning methods have limitations in practicability, generalization and interpretability. The purpose of this work is to overcome the limitations of the above methods and achieve generalized and explicable long-term robot manipulation task planning.

The authors propose a planning method for long-term manipulation tasks that combines the advantages of existing methods and the prior cognition brought by the knowledge graph. This method integrates visual semantic understanding based on scene graph generation, regression planning based on deep learning and multi-level representation and updating based on a knowledge base.

The authors evaluated the capability of this method in a kitchen cooking task and tabletop arrangement task in simulation and real-world environments. Experimental results show that the proposed method has a significantly improved success rate compared with the baselines and has excellent generalization performance for new tasks.

The authors demonstrate that their method is scalable to long-term manipulation tasks with varying complexity and visibility. This advantage allows their method to perform better in new manipulation tasks. The planning method proposed in this work is meaningful for the present robot manipulation task and can be intuitive for similar high-level robot planning.

The purpose of this paper is to develop basic principles of deterministic structural integrity assessment of a component with a crack- or notch-like defect by including safety factors against fracture and plastic collapse in criteria equations of linear and nonlinear fracture mechanics.

The safety factors against fracture are calculated by demanding that the applied critical stress should not be less than the yield stress of the material for a component with a crack or a notch of the acceptable size. Structural integrity assessment of the engineering components damaged by crack- or notch-like defects is discussed from view point of the failure assessment diagram (FAD). The methodology of the FAD has been employed for the structural integrity analysis and assessment of acceptable sizes of throw-thickness notch in a plate under tension and surface longitudinal notch-like defects in a pressure vessel.

Basic equations have been presented to calculate the safety factor against fracture for critical values of the stress intensity factor, crack tip opening displacement (CTOD), the J-integral and the FAD as well as to estimate an acceptable (safe) region for an engineering component with a crack- or notch-like defect of the acceptable size. It was shown that safety factors against fracture depend on both the safety factor against plastic collapse and employed fracture mechanics criterion. The effect of crack/notch tip constraint is incorporated into criteria equations for the calculation of safety factors against fracture.

The deterministic method of fracture mechanics is recommended for structural integrity assessment of a component with a crack- or notch-like defect by including safety factors against fracture and plastic collapse in criteria equations of linear and nonlinear fracture mechanics.