The use of imageless navigation to quantify cutting error in total knee arthroplasty

Purpose Navigated total knee arthroplasty (TKA) improves implant alignment by providing feedback on resection parameters based on femoral and tibial cutting guide positions. However, saw blade thickness, deflection, and cutting guide motion may lead to final bone cuts differing from planned resections, potentially contributing to suboptimal component alignment. We used an imageless navigation device to intraoperatively quantify the magnitude of error between planned and actual resections, hypothesizing final bone cuts will differ from planned alignment. Materials and methods A retrospective study including 60 consecutive patients undergoing primary TKA using a novel imageless navigation device was conducted. Device measurements of resection parameters were obtained via attachment of optical trackers to femoral and tibial cutting guides prior to resection. Following resection, optical trackers were placed directly on the bone cut surface and measurements were recorded. Cutting guide and bone resection measurements of both femoral and tibial varus/valgus, femoral flexion, tibial slope angles, and both femoral and tibial medial and lateral resection depths were compared using a Student's t-test. Results Femoral cutting guide position differed from the actual cut by an average 0.6 ± 0.5° (p = 0.85) in the varus/valgus angle and 1.0 ± 1.0° (p = 0.003) in the flexion/extension angle. The difference between planned and actual cut measurements for medial and lateral femoral resection depth was 1.1 ± 1.1 mm (p = 0.32) and 1.2 ± 1.0 mm (p = 0.067), respectively. Planned cut measurements based on tibial guide position differed from the actual cut by an average of 0.9 ± 0.8° (p = 0.63) in the varus/valgus angle and 1.1 ± 1.0° (p = 0.95) in slope angle. Measurement of medial and lateral tibial resection depth differed by an average of 0.1 ± 1.8 mm (p = 0.78) and 0.2 ± 2.1 mm (p = 0.85), respectively. Conclusions Significant discrepancies between planned and actual femoral bone resection were demonstrated for flexion/extension angle, likely the result of cutting error. Our data highlights the importance of cut verification postresection to confirm planned resections are achieved, and suggests imageless navigation may be a source of feedback that would allow surgeons to intraoperatively adjust resections to achieve optimal implant alignment.

High-Precision Machining Method of Weak-Stiffness Mirror Based on Fast Tool Servo Error Compensation Strategy

Weak-stiffness mirrors are widely used in various fields such as aerospace and optoelectronic information. However, it is difficult to achieve micron-level precision machining because weak-stiffness mirrors are hard to clamp and are prone to deformation. The machining errors of these mirrors are randomly distributed and non-rotationally symmetric, which is difficult to overcome by common machining methods. Based on the fast tool servo system, this paper proposes a high-precision machining method for weak-stiffness mirrors. Firstly, the clamping error and cutting error compensation strategy is obtained by analyzing the changing process of the mirror surface morphology. Then, by combining real-time monitoring and theoretical simulation, the elastic deformation of the weak-stiffness mirror is accurately extracted to achieve the compensation of the clamping error, and the compensation of the cutting error is achieved by iterative machining. Finally, a weak-stiffness mirror with a thickness of 2.5 mm was machined twice, and the experimental process produced a clamping error with a peak to valley (PV) value of 5.2 µm and a cutting error with a PV value of 1.6 µm. The final machined surface after compensation had a PV value of 0.7 µm. The experimental results showed that the compensation strategy proposed in this paper overcomes the clamping error of the weak-stiffness mirror and significantly reduces cutting errors during the machining process, achieving the high precision machining of a weak-stiffness mirror.

Reduction in Rejection Rate of Soy Sauce Packaging via Six Sigma

The Six Sigma methodology is the most powerful quality improvement technique. This research deals with applying the Six Sigma methodology in reducing the rejection rate of soy sauce packaging in food production. The DMAIC methodology of Six Sigma provides a step-by-step quality improvement methodology in which statistical techniques are applied. The leakage and cutting error problems were identified in the Define phase. The extent of the problem was measured in the Measure phase. The current DPMO value was 5,794.39, or sigma level at 4.0245. The root cause of the problem and the improvement priority were identified in the Analyze phase by applying the fishbone diagram and FMEA. The design of new Standard Operating Procedures (SOPs) and preventive maintenance schedule were used in the Improve phase to increase the sigma level by 50-60 percent and decrease DPMO by 99 percent for the upcoming four months implementation. Furthermore, a control plan was provided in the Control phase to monitor and sustain the achieved improvements.

Adjustable Slot Cutting Guide for Improved Accuracy During Bone Resection in Total Knee Arthroplasty

Slotted cutting guides are used by orthopaedic surgeons to improve the accuracy of bone resection during total knee replacement. Accuracy of the saw cuts has an effect on patient mobility and on implant survival time. While computer navigation systems have improved the accuracy of cutting guide placement, the contribution to cutting error from blade toggle within the slots of the cutting guide persists. In this research, equations were derived to quantify angular cutting error based on the parameters affecting blade and cutting guide geometry. Analytically, the relationship between cutting plane error and blade thickness was determined to be linear. A smaller gap, due to thicker blades with minimal tooth offset, results in less cutting error. From an experimental standpoint, six commercially available cutting guides were tested for femoral plane cutting accuracy by resection of synthetic bone under the guidance of computer navigation. The results indicate an average flexion/extension error of 3.8 deg for a 0.89 mm thick blade and 2.0 deg for a 1.27 mm blade. Varus/valgus error due to twisting of the blade within the slot was less than 1.0 deg, regardless of blade thickness. To improve upon cutting accuracy, an adjustable slot cutting guide was designed and tested. From more closely matching slot width to blade thickness, the results indicate that cutting plane error can be reduced to less than 1.0 deg in both the flexion/extension and varus/valgus planes.

Research of Garlic Umbilical (Root) Cutting Machine Based on Image Processing

Currently, cutting umbilical (root) process of dehydrated garlic slice processing plant has not been realized mechanization in China, and mostly completed by manual. Cutting umbilical (root) efficiency is low and the quality is difficult to guarantee. In this paper based on image processing, the demarcation line between garlic umbilical and garlic meat is measured, and then the measured data is transmitted to MCU control system of garlic umbilical (root) cutting machine through serial port communication technology. MCU system controls the gear motor to drive ball screw moving accurately and cutting garlic umbilical. The cutting error is less than 0.5 mm. This system adopts image processing technology and electromechanical integration technology, realizes the automation cutting of garlic umbilical (root).