An error compensation system has been developed to enhance the time-variant volumetric accuracy of a 3-axis machining center by correcting the existing machine errors through sensing, metrology, and computer control techniques. A general methodology has been developed to synthesize both the geometric and thermal errors of machines into a time-variant volumetric error model. Instead of the well-known 21 geometric error components, 32 machine linkage errors are formulated as a 4D error field including the space domain and the time domain. Different types of models are proposed for different kinds of thermal error components. A compensation controller based on an IBM/PC has been linked with a CNC controller to compensate for machine errors in real time. This scheme has been implemented on a horizontal machining center and has been shown, using metrology instruments, to improve the machine accuracy by an order of magnitude. A cut workpiece inspected using a coordinate measuring machine (CMM) has also shown that dimension errors have been reduced from 92.4 μm to 18.9 μm in a dimension of 404 × 310 mm2 and the depth difference of milled surfaces has been reduced from 196 μm to 8 μm.

BackgroundIron overload is recognized as a new pathogenfor osteoporosis. Various studies demonstrated that iron overload could induce apoptosis in osteoblasts and osteoporosis in vivo. However, the exact molecular mechanisms involved in the iron overload-mediated induction of apoptosis in osteoblasts has not been explored.PurposeIn this study, we attempted to determine whether the mitochondrial apoptotic pathway is involved in iron-induced osteoblastic cell death and to investigate the beneficial effect of N-acetyl-cysteine (NAC) in iron-induced cytotoxicity.MethodsThe MC3T3-E1 osteoblastic cell line was treated with various concentrations of ferric ion in the absence or presence of NAC, and intracellular iron, cell viability, reactive oxygen species, functionand morphology changes of mitochondria and mitochondrial apoptosis related key indicators were detected by commercial kits. In addition, to further explain potential mechanisms underlying iron overload-related osteoporosis, we also assessed cell viability, apoptosis, and osteogenic differentiation potential in bone marrow-derived mesenchymal stemcells(MSCs) by commercial kits.ResultsFerric ion demonstrated concentration-dependent cytotoxic effects on osteoblasts. After incubation with iron, an elevation of intracelluar labile iron levels and a concomitant over-generation of reactive oxygen species (ROS) were detected by flow cytometry in osteoblasts. Nox4 (NADPH oxidase 4), an important ROS producer, was also evaluated by western blot. Apoptosis, which was evaluated by Annexin V/propidium iodide staining, Hoechst 33258 staining, and the activation of caspase-3, was detected after exposure to iron. Iron contributed to the permeabilizatio of mitochondria, leading to the release of cytochrome C (cyto C), which, in turn, induced mitochondrial apoptosis in osteoblasts via activation of Caspase-3, up-regulation of Bax, and down-regulation of Bcl-2. NAC could reverse iron-mediated mitochondrial dysfunction and blocked the apoptotic events through inhibit the generation of ROS. In addition, iron could significantly promote apoptosis and suppress osteogenic differentiation and mineralization in bone marrow-derived MSCs.ConclusionsThese findings firstly demonstrate that the mitochondrial apoptotic pathway involved in iron-induced osteoblast apoptosis. NAC could relieved the oxidative stress and shielded osteoblasts from apoptosis casused by iron-overload. We also reveal that iron overload in bone marrow-derived MSCs results in increased apoptosis and the impairment of osteogenesis and mineralization.

This paper is the first attempt to implement a knowledge-based diagnostic approach for the auto-body assembly process launch. This approach enables quick detection and localization of assembly process faults based on in-line dimensional measurements. The proposed approach includes an auto-body assembly knowledge representation and a diagnostic reasoning mechanism. The knowledge representation is comprised of the product, tooling, process, and measurement representations in the form of hierarchical groups. The diagnostic reasoning performs fault diagnostic in three steps. First, an initial statistical analysis of measurement data is performed. Next, the Candidate Component and Candidate Station with the hypothetical fault are searched. Finally, the fault symptom is identified and the root cause is suggested. Two case studies are presented to demonstrate the implementation of the proposed method.

For automatic detection/diagnosis of localized defects in bearings, a pattern recognition analysis scheme was developed for investigating vibration signals of bearings. Two normalized and dimensionless features are extracted by short-time signal processing techniques. Employing these two features, two linear discriminant functions have been established to detect defects on the outer race and rollers of bearings, respectively. Results of fault detection/diagnosis, based on the experimental data of imposed bearing defects, indicated the technique to be 14 percent better in the rate of success for the detection of defects than the best among the state-of-the-art. It takes 20 seconds for data processing and fault diagnosis on a PC-AT on-line implementation.