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Proposes a computationally‐simple method, based on the centroid solid angle, for computing the probability distributions of the natural resting aspects of small parts, the fore‐knowledge of which can improve the design of vibratory feeders and orienting devices. The centroid solid angle (CSA) hypothesis postulates that the probability of a part coming to rest on a particular aspect is directly proportional to the solid angle subtended by the aspect with respect to the centroid (the centroid solid angle) and inversely proportional to the height of the centroid from the aspect in question. When benchmarked against Boothroyd’s energy barrier method, its results did not deviate from those of the energy barrier method by more than 0.04. Examines studies of a cylindrical prismatic part and a symmetrical T‐shaped prism. The drop tests used to obtain the authors’ empirical data were validated by experiments conducted on vibratory bowl feeders, subjected to different vibration frequencies. The tracks of one of the bowls was coated with urethane to simulate a soft surface. In the case of both frequencies, the empirical results are in generally good agreement with the predictions of the CSA hypothesis; the largest deviation was 0.07. As for the urethane track, the largest deviation was 0.08, thereby corroborating the results of the drop test method.

Proposes a new formulation for allocating process tolerances. The major contribution of the model is to assign tolerances with maximization of the conformance rate of the entire process. The cumulative standard normal probability is used to estimate the scrap rate of each operation with respect to the machining accuracy of equipment, therefore, the design engineers are able to predict the failure rate before production. Results of comparison with other methods indicate that the proposed model can cost‐effectively assign tolerances.

Identifying the most probable natural resting orientation of a part, in automatic handling, helps in the effective design of feeder and orientation devices. For parts with complex geometries and topologies, it is not always intuitively apparent what the natural resting probability of each orientation is. The purpose of this paper is to determine, by theoretical methods, the probability of occurrence of each natural resting orientation of eight different typical sector shaped parts.

Probability of natural resting orientations were found using theoretical methods and drop test. Pearson's χ ² test was used to decide whether to accept or reject the expected data by comparing with the observed data.

Irrespective of dimensions and material, the most probable natural resting orientation was the same. Height of drop was influential in the probability of most probable natural resting orientation.

The research does not include objects with minimum thickness (i.e. 2D objects).

The paper shows that determining the most probable natural resting orientation will help designers to design the part feeders effectively.

This paper develops the statistical error analysis model for assembling, to derive measures of controlling the geometric variations in assembly with multiple assembly stations, and to provide a statistical tolerance prediction/distribution toolkit integrated with CAD system for responding quickly to market opportunities with reduced manufacturing costs and improved quality. First the homogeneous transformation is used to describe the location and orientation of assembly features, parts and other related surfaces. The desired location and orientation, and the related fixturing configuration (including locator position and orientation) are automatically extracted from CAD models. The location and orientation errors are represented with differential transformations. The statistical error prediction model is formulated and the related algorithms integrated with the CAD system so that the complex geometric information can be directly accessed. In the prediction model, the manufacturing process (joining) error, induced by heat deformation in welding, is taken into account.

Tolerance assignment plays a vital role in reducing the manufacturing cost, and most optimization models for assigning the tolerances tend to ignore the process capability of the machine. Therefore, the quality loss due to nonconforming parts can be unacceptably high. Proposes a non‐linear mathematical programming model for determining the component tolerances by simultaneously formulating the component’s manufacturing cost, the machine’s process capability and scrap rate. Includes a comparison between the results obtained by the proposed model and the traditional method.

The purpose of this paper is to obtain the reasonable dimensioning for each part and a full-dimension model of assembly dimensions.

The relational path graph of assembly dimension, the shortest-path spanning tree of functional dimension and a revised spanning tree are established in this paper.

The proposed method can obtain reasonable dimensioning of parts and establishment of dimension model in an assembly.

The proposed method can easily realise by computer and be more suitable to automatic dimensioning and establishment of dimension model of parts.

In an industrial robotic cell, the optimal layout planning problem needs critical analysis, as it indirectly affects the manufacturing time and cost involved in the production process. This paper aims to propose a generic three-step robotic cell layout planning method and aims to enhance the adaptability of robotic manufacturing cell in small-scale industries.

The method uses the data generated from the point cloud modeling and simulation of the objects (machines and robot) to optimize their positions and orientations in the cell. The simulated annealing algorithm has been used to solve the optimization problem with minimum joint displacement criterion. This approach is critically analyzed and discussed against the data collected from an industrial robotic cell in a foundry shop of a pipe manufacturing industry.

More than 50 per cent reduction in the net joint movement of the robot has been achieved. Immediate feedback of the results by a three-dimensional view of the optimal cell layout without using any commercial robotic simulation package.

The layout optimization of an industrial robotic cell based on the point cloud modeling of its objects is the novelty of the method.

The spatial representation technique is an efficient method for packing boxes into a container; however, it has a limitation in dealing with constraints. For practical applications, there are however limitations when dealing with constraints. These constraints provide flexibility for the user to decide which boxes should be placed first. After imposing the initial conditions, the optimisation packing algorithm based on the spatial representation technique ensures that the boxes remaining in the item list are packed as efficiently as possible into the container. The packing plan is then generated during the run time to provide visualisation of the result of actual packing sequences. It also simultaneously outputs a graphical file to the Autocad software for printing and detailed study. The program can be implemented under either the DOS platform or the Windows platform on an IBM PC. The performance is evaluated using data from another algorithm. The results confirm that the enhanced algorithm can manage the user‐specified constraints with good volume utilisation.

In the context of fixed-wing aircraft wing assembly, there is a need for a rapid and precise measurement technique to determine the center distance between two double-hole components. This paper aims to propose an optical-based spatial point distance measurement technique using the spatial triangulation method. The purpose of this paper is to design a specialized measurement system, specifically a spherically mounted retroreflector nest (SMR nest), equipped with two laser displacement sensors and a rotary encoder as the core to achieve accurate distance measurements between the double holes.

To develop an efficient and accurate measurement system, the paper uses a combination of laser displacement sensors and a rotary encoder within the SMR nest. The system is designed, implemented and tested to meet the requirements of precise distance measurement. Software and hardware components have been developed and integrated for validation.

The optical-based distance measurement system achieves high precision at 0.04 mm and repeatability at 0.02 mm within a range of 412.084 mm to 1,590.591 mm. These results validate its suitability for efficient assembly processes, eliminating repetitive errors in aircraft wing assembly.

This paper proposes an optical-based spatial point distance measurement technique, as well as a unique design of a SMR nest and the introduction of two novel calibration techniques, all of which are validated by the developed software and hardware platform.

This study aims to use nanofluid-based minimum quantity lubrication (NMQL) technique to minimize the use of cutting fluids in machining of Inconel-625 and Stainless Steel 304 (SS-304) (Ni-Cr alloys).

Machining of Ni-Cr-based alloys is very challenging as these exhibit lower thermal conductivity and rapid work hardening. So, these cannot be machined dry, and a suitable cutting fluid has to be used. To improve the thermal conductivity of cutting fluid, multi-walled carbon nanotubes (MWCNTs) were added to the soybean oil and used with MQL. This study attempts to compare tool wear of coated carbide inserts during face milling of Inconel-625 and SS-304 under dry, flooded and NMQL conditions. The machining performance of both materials, i.e. Inconel-625 and SS-304, has been compared on the basis of tool wear behavior evaluated using scanning electron microscopy-energy dispersive spectroscopy.

The results indicate higher tool wear and lower tool life during machining of Inconel-625 as compared to SS-304. Machining of Inconel-625 exhibited non-consistent tool wear behavior. The tool failure modes experienced during dry machining are discrete fracture, cracks, etc., which are completely eliminated with the use of NMQL machining. In addition, less adhesion wear and abrasion marks are noticed as compared to dry and flooded machining, thereby enhancing the tool life.

Inconel-625 and SS-304 have specific applications in aircraft and aerospace industry, where sculptured surfaces of the turbine blades are machined. The results of current investigation will provide a rich data base for effective machining of both materials under variety of machining conditions.

The literature review indicated that majority of research work on MQL machining has been carried out to explore machining of Ni-Cr alloys such as Inconel 718, Inconel 800, AISI4340, AISI316, AISI1040, AISI430, titanium alloys, hardened steel alloys and Al alloys. Few researchers have explored the suitability of nanofluids and vegetable oil-based cutting fluids in metal cutting operation. However, no literature is available on face milling using nanoparticle-based MQL during machining Inconel-625 and SS-304. Therefore, experimental investigation was conducted to examine the machining performance of NMQL during face milling of Inconel-625 and SS-304 by using soybean oil (vegetable oil) with MWCNTs to achieve ecofriendly machining.