A unifying framework for tolerance analysis in sensing, design, and manufacturing

Journal ArticleIn this work we address the problem of tolerance representation and analysis across the domains of industrial inspection using sensed data, CAD design, and manufacturing. Instead of using geometric primitives in CAD models to define and represent tolerances, we propose the use of stronger methods that are completely based on the manufacturing knowledge for the objects to be inspected. We guide our sensing strategies based on the manufacturing process plans for the parts that are to be inspected and define, compute, and analyze the tolerances of the parts based on the uncertainty in the sensed data along the different toolpaths of the sensed part. We believe that our new approach is the best way to unify tolerances across sensing, CAD, and CAM, as it captures the manufacturing knowledge of the parts to be inspected, as opposed to just CAD geometric representations

12th CIRP Conference on Computer Aided Tolerancing

The purpose of this paper is to decipher the process of modelling driving to the product behaviour simulation. A simple example of simulation, tolerance stackup, allows illustrating this process. The tolerance stackup is used daily in industry, however, designers do they know exactly what they do? Are they aware of the assumptions they are introducing? To answer to these questions, concepts of GeoSpelling and of GPS ISO standards such as skin model, operations, operators and other concept are introduced such as finite and infinite models

Investigation on the sampling size optimisation in gear tooth surface measurement using a Co-ordinate Measuring Machine

Co-ordinate Measuring Machines (CMMs) are widely used in gear manufacturing industry. One of the main issues for contact inspection using a CMM is the sampling technique. In this paper the gear tooth surfaces are expressed by series of parameters and inspection error compensation and initial value optimisation method are presented. The minimum number of measurement points for 3D tooth surfaces are derived. If high precision is required, more points need to be inspected. The sampling size optimisation is obtained from the criterion equation. The surface form deviation and initial values are optimised using the minimum zone method and Genetic Algorithms. A feature based inspection system for spur/helical gears is developed and trials and simulations demonstrated the developed method is very effective and suitable

NASA space station automation: AI-based technology review

Research and Development projects in automation for the Space Station are discussed. Artificial Intelligence (AI) based automation technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics. AI technology will also be developed for the servicing of satellites at the Space Station, system monitoring and diagnosis, space manufacturing, and the assembly of large space structures

Maintenance Strategies to Reduce Downtime Due to Machine Positional Errors

Manufacturing strives to reduce waste and increase Overall Equipment Effectiveness (OEE). When managing machine tool maintenance a manufacturer must apply an appropriate decision technique in order to reveal hidden costs associated with production losses, reduce equipment downtime competently and similarly identify the machines’ performance. Total productive maintenance (TPM) is a maintenance program that involves concepts for maintaining plant and equipment effectively. OEE is a powerful metric of manufacturing performance incorporating measures of the utilisation, yield and efficiency of a given process, machine or manufacturing line. It supports TPM initiatives by accurately tracking progress towards achieving “perfect production.” This paper presents a review of maintenance management methodologies and their application to positional error calibration decision-making. The purpose of this review is to evaluate the contribution of maintenance strategies, in particular TPM, towards improving manufacturing performance, and how they could be applied to reduce downtime due to inaccuracy of the machine. This is to find a balance between predictive calibration, on-machine checking and lost production due to inaccuracy. This work redefines the role of maintenance management techniques and develops a framework to support the process of implementing a predictive calibration program as a prime method to supporting the change of philosophy for machine tool calibration decision making. Keywords—maintenance strategies, down time, OEE, TPM, decision making, predictive calibration

Improving elevation resolution in phased-array inspections for NDT

The Phased Array Ultrasonic Technique (PAUT) offers great advantages over the conventional ultrasound technique (UT), particularly because of beam focusing, beam steering and electronic scanning capabilities. However, the 2D images obtained have usually low resolution in the direction perpendicular to the array elements, which limits the inspection quality of large components by mechanical scanning. This paper describes a novel approach to improve image quality in these situations, by combining three ultrasonic techniques: Phased Array with dynamic depth focusing in reception, Synthetic Aperture Focusing Technique (SAFT) and Phase Coherence Imaging (PCI). To be applied with conventional NDT arrays (1D and non-focused in elevation) a special mask to produce a wide beam in the movement direction was designed and analysed by simulation and experimentally. Then, the imaging algorithm is presented and validated by the inspection of test samples. The obtained images quality is comparable to that obtained with an equivalent matrix array, but using conventional NDT arrays and equipments, and implemented in real time.Fil: Brizuela, Jose David. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Camacho, J.. Consejo Superior de Investigaciones Científicas; EspañaFil: Cosarinsky, Guillermo Gerardo. Comisión Nacional de Energía Atómica; ArgentinaFil: Iriarte, Juan Manuel. Comisión Nacional de Energía Atómica; ArgentinaFil: Cruza, Jorge F.. Consejo Superior de Investigaciones Científicas; Españ

Automating Robot Planning Using Product and Manufacturing Information

AbstractAdvances in sensing, modeling, and control have made it possible to increase the accuracy of robots, and enable them to perform in dynamic environments. Often, performance deficiencies are not evident until late in the development of the manufacturing process, which delays the beginning of production and may cause damage to parts that have already undergone costly manufacturing steps. The goal of this research is to determine if a robot can meet manufacturing requirements, how to optimally plan robot activities, and to monitor robot processes to track performance. To achieve this, representations of product and manufacturing information and robot capabilities should be carried through the design, process planning, production, and analysis phases. Standards for the exchange of this information have been developed, such as ISO 10303 Part 242 for semantic product and manufacturing information and device kinematics, and the Robot Operating System Industrial specification for robot modeling, path planning, and execution. This paper surveys the relevant technologies and standards needed to enable automated deployment of robots in new application areas

VR-PMS: a new approach for performance measurement and management of industrial systems

A new performance measurement and management framework based on value and risk is proposed. The proposed framework is applied to the modelling and evaluation of the a priori performance evaluation of manufacturing processes and to deciding on their alternatives. For this reason, it consistently integrates concepts relevant to objectives, activity, and risk in a single framework comprising a conceptual value/risk model, and it conceptualises the idea of value- and risk based performance management in a process context. In addition, a methodological framework is developed to provide guidelines for the decision-makers or performance evaluators of the processes. To facilitate the performance measurement and management process, this latter framework is organized in four phases: context establishment, performance modelling, performance assessment, and decision-making. Each phase of the framework is then instrumented with state of-the-art quantitative analysis tools and methods. For process design and evaluation, the deliverable of the value- and risk-based performance measurement and management system (VR-PMS) is a set of ranked solutions (i.e. alternative business processes) evaluated against the developed value and risk indicators. The proposed VR-PMS is illustrated with a case study from discrete parts manufacturing but is indeed applicable to a wide range of processes or systems