A Method to Determine the Optimal Checking-Fixture Layout for Gauge Repeatability

This paper proposes a method for finding the optimal fixture layout to achieve acceptable gauge repeatability in the inspection process of a non-rigid part. Currently, there are no rigorous means of evaluating the effectiveness of a fixture layout for a part in terms of gauge repeatability until actual parts and gauges are available late in the product development process. Changes to the part design or modifications to the gauge at this late stage are usually costly and can result in program delays, incurring substantial costs. This paper proposes an approach to arrive at the best locator layout for gauge repeatability early in the part design phase thereby avoiding costly and time-consuming changes during the build phase. The method is implemented using a commercially available tolerance stack software with finite element analysis combined with a specially coded genetic algorithm. The method’s effectiveness is demonstrated through the improvement in gauge repeatability from an arbitrary datum scheme to the optimal datum scheme in a notional design problem as well as an actual production part. We also demonstrate that the commonly accepted datum scheme of using a primary plane along the largest dimension of a part may be highly suboptimal for gauge repeatability.

A Method to Predict the Sheet Metal Deformation under Different Locator Layout

"N-2-1" principle is widely recognized in the fixture design for deformable sheet metal workpieces, where N, the locators on primary datum, is the key to sheet metal fixture design. However, little research is done on how to determine the positions of N locators when considering normal deviation. This paper, concerning the low efficiency of the locating point optimization method using the finite element model, proposes a GA-BP neural network to predict the sheet metal deformation under different locator layout, by which to calculate the clamp normal deviation. Finally, a case is used to illustrate the flowchart of GA-BP network. Results show that the method has good performance and prediction ability.

Locator Layout Optimization for Checking Fixture Design of Thin-Walled Parts

The location of a checked part is one of the most critical and complicated problems in the checking fixture design (CFD) for thin-walled parts with less stiffness. The unreasonable layout of locators will give rise to the high deflection of the checked part and affect measure accuracy. Based on the “N-2-1” locating principle, an optimization method is presented to determine the locator layout, where the finite element method (FEM) is used to calculate the maximal deformation of the work piece which is used to be an objective function of optimization, and the Particle Swarm Optimization (PSO) with fine performance of global convergence is adopted as an optimization solver to seek for the optima. Finally, a case study is presented to verify the proposed method.

A New Approach for Automation of Locating Planning of Workpiece

Fixtures are used to locate and constrain firmly a workpiece during machining operation. Flexible and efficient fixturing has become an important issue in flexible manufacturing systems and computer integrated manufacturing system. Locating planning is the basis of the fixturing design, which has a direct influence on the quality of the clamping scheme and the machining quality of workpiece. This paper presents a new approach for locating planning of workpiece. Firstly, it will automatically select the primary locating surfaces with consideration of 5 influence factors: constraint freedoms, surface feature, valid locating area, tolerance relationship and surface roughness. Then the other locating surfaces are determined by retrieving similar workpieces under the guideline of 4 locating methods which will make the best of already available locating planning. Finally the optimal locator layout is fast achieved with GA with the goal of minimal locating tolerance.

Robust Fixture Layout Design for a Product Family Assembled in a Multistage Reconfigurable Line

Reconfigurable assembly systems enable a family of products to be assembled in a single system by adjusting and reconfiguring fixtures according to each product. The sharing of fixtures among different products impacts their robustness to fixture variation due to trade offs in fixture design (to allow the accommodation of the family in the single system) and to frequent reconfigurations. This paper proposes a methodology to achieve robustness of the fixture layout design through an optimal distribution of the locators in a multistation assembly system for a product family. This objective is accomplished by (1) the use of a multistation assembly process model for the product family, and (2) minimizing the combined sensitivity of the products to fixture variation. The optimization considers the feasibility of the locator layout by taking into account the constraints imposed by the different products and the processes (assembly sequence, data scheme, and reconfigurable tools’ workspace). A case study where three products are assembled in four stations is presented. The sensitivity of the optimal layout was benchmarked against the ones obtained using dedicated assembly lines for each product. This comparison demonstrates that the proposed approach does not significantly sacrifice robustness while allowing the assembly of all products in a single reconfigurable line.