Roundness: A closed form upper bound for the centroid to minimum zone center distance by worst-case analysis

The minimum zone tolerance (MZT) meets the ISO 1101 definition of roundness error: it determines two concentric circles that contain the roundness profile and such that the difference in radii is the least possible value. This article provides theoretical evidence that the minimum size of the neighborhood of the centroid containing the minimum zone center is pi E-1(C), where E-C is the roundness error related to the centroid, which can be evaluated in closed form. The implications of such linear estimating are twofold: (i) locating the part center with a given tolerance, e.g. for manufacturing tasks, such as handling (peg-hole) or machining (centering) and (ii) providing a search area for minimum zone center-based algorithms, such as metaheuristics (GA, PSO, etc.)

Native metaheuristics for non-permutation flowshop scheduling

The most general flowshop scheduling problem is also addressed in the literature as non-permutation flowshop (NPFS). Current processors are able to cope with the combinatorial complexity of (n!)exp m. NPFS scheduling by metaheuristics. After briefly discussing the requirements for a manufacturing layout to be designed and modeled as non-permutation flowshop, a disjunctive graph (digraph) approach is used to build native solutions. The implementation of an Ant Colony Optimization (ACO) algorithm has been described in detail; it has been shown how the biologically inspired mechanisms produce eligible schedules, as opposed to most metaheuristics approaches, which improve permutation solutions. ACO algorithms are an example of native non-permutation (NNP) solutions of the flowshop scheduling problem, opening a new perspective on building purely native approaches. The proposed NNP-ACO has been assessed over existing native approaches improving most makespan upper bounds of the benchmark problems from Demirkol et al. (1998)

Monitoring critical points in robot operations with an artificial vision system

Stereo Vision for assisted robot operations implies the use of special purpose techniques to increase precision. A simple algorithm in the reconstruction of 3D trajectories by real-time tracking is described here, which has been extensively tested with promising results. If the form of the trajectory is known a priori, the interpolation of multiple real-time acquisition yields an increase of precision of about 25% of the initial error, depending on the uncertainty in locating the points within the image. The experimental tests which have been performed concern the case of a straight trajectory

The quality control of natural materials: defect detection on Carrara marble with an artificial vision system

A feasibility study of automatic defect detection on stone products with artificial vision tech-niques has been carried out. A general outlook of available defect types is given. A suitable lighting system with the main requirements is described. Several algorithms have been de-signed in order to detect the defective material. Experimental tests have been performed on commercial Carrara marble tiles

Gripping by controllable wet adhesion using a magnetorheological fluid

The magnetorheological properties of ferrofluids (or smart, or active fluids) are well known, and are currently exploited in shear in advanced damping systems in the automotive industry, robotics (prosthesis), and machine tools (chatter reduction, positioning). This paper proposes an end effector for gripping by a novel form of controllable wet adhesion inspired by gastropod pedal mucus. The design of a gripper has been proposed, along with performance analysis based on experiments on various parameters, materials and surfaces, exhibiting robustness in unknown and dirty environment, typical of disassembly. Benefits over competing handling technologies and future research directions in this new area have been addressed

Optimal blind sampling strategy for minimum zone roundness evaluation by metaheuristics

The minimum zone tolerance is a non linear method to find a global solution to the roundness evaluation problem. Metaheuristics such as genetic algorithms, ant colony systems and particle swarm optimization concurrently process a set of solution candidates (chromosomes, ants, particles etc.) within a given search-space. Computation experiments carried out with an effective genetic algorithm have shown that the optimal sampling strategy providing sufficient accuracy at acceptable processing time represents a compromise between number of sample points and search-space size. An estimate of the neighborhood of the centroid containing the minimum zone center is given

Nonpermutation flow line scheduling by ant colony optimization

A flow line is a conventional manufacturing system where all jobs must be processed on all machines with the same operation sequence. Line buffers allow nonpermutation flowshop scheduling and job sequences to be changed on different machines. A mixed-integer linear programming model for nonpermutation flowshop scheduling and the buffer requirement along with manufacturing implication is proposed. Ant colony optimization based heuristic is evaluated against Taillard's (1993) well-known flowshop benchmark instances, with 20 to 500 jobs to be processed on 5 to 20 machines (stages). Computation experiments show that the proposed algorithm is incumbent to the state-of-the-art ant colony optimization for flowshop with higher job to machine ratios, using the makespan as the optimization criterion

Scheduling flow lines with buffers by ant colony digraph

This work starts from modeling the scheduling of n jobs on m machines/stages as flowshop with buffers in manufacturing. A mixed-integer linear programing model is presented, showing that buffers of size n - 2 allow permuting sequences of jobs between stages. This model is addressed in the literature as non-permutation flowshop scheduling (NPFS) and is described in this article by a disjunctive graph (digraph) with the purpose of designing specialized heuristic and metaheuristics algorithms for the NPFS problem. Ant colony optimization (ACO) with the biologically inspired mechanisms of learned desirability and pheromone rule is shown to produce natively eligible schedules, as opposed to most metaheuristics approaches, which improve permutation solutions found by other heuristics. The proposed ACO has been critically compared and assessed by computation experiments over existing native approaches. Most makespan upper bounds of the established benchmark problems from Taillard (1993) and Demirkol, Mehta, and Uzsoy (1998) with up to 500 jobs on 20 machines have been improved by the proposed ACO

Minimal Exhaustive Search Heuristics (MESH) of point clouds for form tolerances: The minimum zone roundness

MESH is an ε-approximate algorithm to find the minimum zone center of a given roundness profile, with ε = 10-d, where d is the number of required decimal digits. The proposed MESH algorithm is able to provide only the accuracy that is necessary to find the minimum zone error roundness (circularity). The basic principle is to exhaustively assess all MZR center candidates located at the cross points of a mesh, with spacing directly related to the target accuracy. Criteria for the selection of the required manufacturing (designer's) target accuracy (product specifications) are discussed. This result has been made possible by previous work on the limit search space to be searched. The algorithm effectiveness has been shown by computation experiments up to 16,384 cloud datapoints and by comparison with genetic algorithms and an exact method from the literature. The MESH algorithm can also serve for benchmarking purposes to assess the performance of other algorithms in terms of both accuracy and speed. The extension to other form tolerances of the exhaustive mesh based approach is discussed