E. Amine Lehtihet

Error compensation for fused deposition modeling (FDM) machine by correcting slice files

Purpose – The purpose of this research is to extend the previous approach to software error compensation to fused deposition modeling (FDM) machines and explores the approach to apply compensation by correcting slice files.Design/methodology/approach – In addition to applying the stereolithography (STL) file‐based compensation method from earlier research; a new approach using the slice file format to apply compensation is presented. Under this approach, the confounded effects of all errors in a FDM machine are mapped into a “virtual” parametric machine error model. A 3D artifact is built on the FDM machine and differences between its actual and nominal dimensions are used to estimate the coefficients of the error functions. A slice file compensation method is developed and tested on two types of parts as a means for further improving the error compensation for feature form error improvement. STL file compensation is also applied to a specific FDM 3000 machine and the results are compared with those of a ...

Parametric error modeling and software error compensation for rapid prototyping

This paper is motivated by the need for a generic approach to evaluate the volumetric accuracy of rapid prototyping (RP) machines. The approach presented in this paper is inspired in large part by the techniques developed over the years for the parametric evaluation of coordinate measuring machine (CMM) errors. In CMM metrology, the parametric error functions for the machine are determined by actual measurement of a master reference artifact with known characteristics. In our approach, the RP machine is used to produce a generic artifact, which is then measured by a master CMM, and measurement results are used to infer the RP machines parametric error functions. The results presented demonstrate the feasibility of such an approach on a two‐dimensional model.

A classification algorithm and optimal feature selection methodology for automated solder joint defect inspection

Abstract A classification algorithm and optimal feature selection methodology are developed for implementation on an automated solder defect inspection system. Computer-generated three-dimensional geometric models of solder joint defects are used to train the system and simulate defect classification. System performance is assessed through simulation and is shown to be successful at classification of dominant solder defects, including simultaneously occurring defects and overlapping defect classes.

An implicit enumeration approach to tolerance allocation in sequential tolerance control

The accuracy and precision of a manufactured dimension is largely dependent on the accuracy and precision of the technological processes selected for its execution. It is not unusual to have available several competing technological processes for execution of each manufacturing operation specified in a process plan, where it is generally assumed that as the precision of the technological process improves, the associated cost and yield of the operation increase. This paper presents an implicit enumeration approach to the selection of an optimum subset of technological processes required to execute a process plan under a. sequential (or adaptive) tolerance control strategy.

A comparative evaluation of sequential set point adjustment procedures for tolerance control

The machining of complex parts typically involves a logical and chronological sequence of n operations on m machine tools. Because manufacturing datums cannot always match design datums, some of the design specifications imposed on the part are usually satisfied by distinct subsets of the n operations prescribed in the process plan. Conventional tolerance control specifies a fixed set point for each operation and permissible variation about this set point to insure compliance with the specifications. Sequential tolerance control (STC) uses real-time measurement information at the completion of one stage to exploit the available space inside a dynamic feasible zone and reposition the set point for subsequent operations. This paper introduces an extension of STC that utilizes the variability of the operations to scale the problem data and further enhance the ability of STC to optimize the production of an acceptable part.

A probabilistic search method for sequential tolerance control

Tolerance control is the set of practices used to ensure that parts are made within their specifications. Sequential Tolerance Control (STC) is the practice of using the results of earlier operations in the execution of a process plan to locate appropriate set points for later operations. In a previously developed set-point adjustment method, the largest sphere that fits into the remaining feasible space is moved to its extreme positions in the coordinate direction of the next operation, x k , and the next set point is positioned at the mean of the k th coordinates of the centres in these two positions. Scaling the feasible space in proportion to the variability of each operation has also been investigated. This paper presents a probabilistic search method for STC. This method finds the new set point by using the Nelder-Mead downhill simplex method to optimize an estimation of the expected process yield. Probabilistic search is found to be about as effective as sphere-fitting methods for normally distributed process deviations, but for skewed distributions, the search method is shown to yield better set points than previous methods.

Tolerance design of datum systems

A majority of mechanical products and devices can be viewed as a collection of parts engineered to assemble so that mating parts and features satisfy some predetermined spatial relationships. Designers typically satisfy the constraints that arise from these relationships by using a set of specific physical features to create on each mating part an accurate reference frame from which all other relevant geometric elements are located. The accuracy and precision with which two mating parts assemble and influence subsequent alignment of other features are controlled by the nominal dimensioning and tolerancing scheme imposed on the geometric elements used to create the two coincident reference frames. The paper presents the development and implementation of a computer aid to assist designers in the allocation of design sizes and tolerances that satisfy functional translation, rotation and assembly constraints imposed on four datum systems commonly used in design.

On the frequency and location of set point adjustments in sequential tolerance control

Sequential tolerance control (STC) is an approach that uses real-time measurement information at the completion of a stage to exploit the available space inside a dynamic feasible zone and reposition the set points for the remaining operations. STC has been shown to produce significantly higher yields than conventional tolerance control given constant equipment precision. STC was developed under the premise that a measurement and set point adjustment would follow each operation. However, measuring after each operation may not be practical under certain conditions. This study develops techniques for determining when measurements and set point adjustments should take place so that the benefits of STC are realized without interrupting the process after every operation.

An implicit enumeration approach to probabilistic tolerance allocation under conventional tolerance control

The accuracy and precision of a manufactured dimension is largely dependent on the accuracy and precision of the technological processes selected for its execution. It is not unusual to have available several competing technological processes for execution of each manufacturing operation specified in a process plan, where it is generally assumed that, as the precision of the technological process improves, the associated cost and yield of the operation increase. This paper presents an implicit enumeration approach to the selection of an optimum subset of technological processes required to execute a process plan under a conventional tolerance control strategy. A probabilistic approach to the problem is presented and the First Order Second Moment Method (FOSMM) is used to estimate yield for an interdependent system of functional requirements.

A unified framework for probabilistic sequential tolerance control

Sequential tolerance control (STC) is a methodology that uses available measurement information at the completion of one manufacturing operation to position the set point for subsequent operations. It has been shown that STC can lead to inferior solutions when the manufacturing process distributions are skewed. This paper presents an adaptive sphere-fitting method (ASF-STC) that adjusts for such skewness. ASF-STC requires as inputs both the direction of skewness and the probability distribution parameters for each operation. Heuristic methods for estimating each of these inputs are presented. Through computational testing, ASF-STC is shown to offer significant improvements over STC when such skewness exists.