A Comparative Study of AC and MFDC Resistance Spot Welding

This paper presents a comparative study of the AC and MFDC resistance spot welding process. Two identical welders were used; one with a single phase AC and the other with a median frequency DC weld control. Both welders were instrumented such that the primary and secondary voltage and current could be collected. A nugget growth experiment was conducted to compare the weld size and energy consumption in the AC and MFDC welding processes. It is found that the MFDC process generally produces larger welds with the same welding current. However, this difference is more prominent when the welding current is low. Overall the AC welding process consumes more energy to make a same size weld. The larger the welding current is used, the less efficient the AC process becomes.

A Comparison of Generator Mode on the Performance of Finish EDM of AISI P20 Tool Steel

The AISI P20 steel is applied by the tooling industry as material for injection molding tools. It is known that the EDM process parameters technology installed at the majority of CNC EDM machines do not cover some of the necessities of the tooling industry. So, the customers are required to develop their own process parameters. In order to provide useful technical information to the industry an experimental investigation on the EDM of the AISI P20 tool steel under finish machining has been carried out. The material removal rate Vw, volumetric relative wear v and workpiece surface texture Ra, which are representative of EDM performance aspects, were analyzed against the variation of some of the most important EDM electrical variables using copper tool electrodes under positive and negative polarity. The EDM machine generator was also programmed to actuate under isoenergetic mode and relaxation mode. The results are discussed and some appropriate parameters for EDM of AISI P20 are suggested.

Tool Selection and Path Control for Automated Posterior Teeth Coronal Canal Treatment Preparation

This paper represents a part of research plan of “Advanced Endodontic Technology Development.” In order to aid endodontic treatment a 3-D computer model of root canals has been created which shows the geometrical characteristics. The extent of work needed for root canal treatment is obtained from this 3-D model. The objective of this paper is to convert the geometrical characteristics into automatic treatment procedure planning. This computer-aided process planning for endodontic treatment determines tool selection and process method. It also calculates tool path and optimum tool movement distance. The output of this planning system is a numerical controlled program. Because of paper size limitation, only tool selection and path control during coronal canal treatment preparation for posterior teeth are discussed in the paper. The computer-aided treatment procedure planning system provides transformation from a 3-D canal model to a machine-controlled program that will yield a treated root canal ready for filling. It serves as a bridge between design (3-D canal model) and manufacturing (canal treatment). Unlike conventional methods for root canal treatment, the computer-aided treatment process planning system emphasizes a non-destructive internal tooth geometry examination and less invasive access preparation.

Micro Thin Film Sensor Embedding in Metals by Ultrasonic Welding for Production of Miniature Smart Tooling

This work is to study micro thin film sensor embedding in metals for the production of miniature smart tooling. This technique promises to significantly improve the safety and reliability for manufacturing processes and reduce operation costs. One key concern of the current research is to investigate if sensor functionality can be maintained during and after embedding in metals by use of ultrasonic welding (USW), which could be hostile to micro thin film thermocouples (TFTCs) embedded near the welding interface. The welding workpieces, consisting of a nickel strip with embedded micro sensors and a copper thin sheet, were welded by USW process. Experimental results showed that TFTCs survived the ultrasonic welding process. The embedded TCFCs were also capable of measuring temperature in-situ near the weld interface during the embedding process.

Fabrication of Polycaprolactone Bone Tissue Engineering Scaffolds Using Selective Laser Sintering

Tissue engineering combines principles of the life sciences and engineering to replace and repair damaged human tissue. Present practice generally requires the use of porous, bioresorbable scaffolds to serve as temporary 3D templates to guide cell attachment, differentiation, proliferation, and subsequent regenerate tissue formation. Such scaffolds are anticipated to play an important role in allowing physicians to simultaneously reconstruct and regenerate damaged human tissue such as bone, cartilage, ligament and tendon. Recent research strongly suggests the choice of scaffold material and its internal porous architecture significantly influence regenerate tissue structure and function. However, a lack of versatile biomaterials processing and fabrication methods capable of meeting the complex geometric and compositional requirements of tissue engineering scaffolds has slowed progress towards fully testing these promising findings. It is widely accepted that layered manufacturing methods such as selective laser sintering (SLS) have the potential to fulfill these needs. Our research aims to investigate the viability of using SLS to fabricate tissue engineering scaffolds composed of polycaprolactone (PCL), one of the most widely investigated biocompatible, bioresorbable materials for tissue engineering applications. In this work, we report our recent progress on porous scaffold design and fabrication, optimal SLS processing parameter development using systematic factorial design of experiments, and structural characterization via optical microscopy.

The Role of Cutter Eccentricity on Surface Finish and Milling Forces

In this paper, the role of milling cutter eccentricity, commonly referred to as runout, is explored to determine its effects on surface topography and milling forces. This work is motivated by the observation that commercially-available cutter bodies often exhibit variation in the teeth/insert radial locations as a result of manufacturing issues. Consequently, the chip load on individual cutting teeth varies periodically, which can lead to premature failure of the cutting edges. Additionally, this chip load variation increases the roughness of machined surfaces. This research isolates the effect of runout on cutting forces and the machined surface finish in a series of experiments completed on a precision milling machine with 0.1 μm positioning repeatability and 0.02 μm spindle error motion. The runout is varied in a controlled fashion and results compared between experiment and a comprehensive time-domain simulation.

Tribological Influences of TiAlN Coating on Tool Wear for High-Speed Dry and Wet Machining of Steels

The tribological influences of PVD-applied TiAlN coatings on the wear of cemented carbide inserts and the microstructure wear behaviors of the coated tools under dry and wet machining are investigated. The turning test was conducted with variable high cutting speeds ranging from 210 m/min to 410m/min. The analyses based on the experimental results lead to strong evidences that conventional coolant has a retarded effect on TiAlN coatings under high-speed machining. Microwear mechanisms identified in the tests through SEM micrographs include edge chipping, micro-abrasion, micro-fatigue, micro-thermal, and micro-attrition. These micro-structural variations of coatings provide structure-physical alterations as the measures for wear alert of TiAlN coated tool inserts under high speed machining of steels.

Adaptive Control and Monitoring Using the Spindle Integrated Force Sensor System

Applications of spindle integrated force sensors are examined where the cutting forces are reconstructed from the piezoelectric force sensors that are imbedded in the spindle housing. The reconstruction of the cutting forces using the disturbance Kalman filter effectively provides the high bandwidth sensor requirements. The three applications that are presented in this paper are Adaptive Control with Constraint (ACC), chatter detection, and tool breakage detection, all using the spindle integrated sensors. ACC provides effective means of increasing machining productivity through the adjustment of feed rates by constraining cutting forces. The detection of chatter vibration in machining operations is important in order to ensure quality surface finishes. The cutting forces measured from the spindle sensors provide sufficient information as to whether the cutting operations are stable or not. Tool breakage detection is performed using both a good tool and a damaged tool. Two residual indices based on the first order auto-regressive (AR) filter are examined to determine tool breakage. The experiments verify the successful monitoring strategies using the spindle integrated force sensors.

Computer Aided Dynamic Analysis of the Drive of a Chain Conveyor

Literature indicates availability of dynamic analysis of a drive shaft of a chain conveyor in a limited way. Relations for estimation of a conveyor chain pull to overcome, (i) Rolling resistance of the track, (ii) Tail sprocket and drive sprocket shaft bearing friction resistances, (iii) Drive and tail sprocket chain binding resistances and (iv) Impact loading on the chain have been only derived [1,2]. However, further extension to deduce the load torque demand on drive sprocket during one articulation of the chain is not seen derived in the literature. This paper details this, followed by digital computer simulation including illustration of application of this new procedure to a representative case study. Work on the same lines is not much seen in the literature. However, similar work by Harrison [4] is done for the belt conveyor.

Performance Similarity Based Method for Enhanced Prediction of Manufacturing Process Performance

Full realization of all potentials in predictive and proactive maintenance highly depends on the accuracy of long-term predictions of the remaining useful life of manufacturing equipment. Parametric linear prediction techniques, such as Autoregressive Moving Average modeling (ARMA), are routinely used to trend and predict future behavior of any time series, but are frequently not appropriate for long-term prediction because of the highly complicated and non-stationary nature of manufacturing processes. In this paper, we propose a novel method that is capable of achieving high long-term prediction accuracy by comparing signatures from two degradation processes using measures of similarity that form a Match Matrix. Through this concept, we can effectively include large amounts of historical information into the prediction of the current degradation process. Similarities with historical records are used to generate possible future distributions of features, which is then used to predict probabilities of failure over time by evaluating overlaps between predicted feature distributions and feature distributions related to unacceptable equipment behavior. Experimental results show that the proposed method results in a significant improvement of long-term prediction accuracy compared with ARMA modeling-based prediction.