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This paper presents a machining accuracy analysis for computer-aided fixture design verification. While discussing the utilization of CNC machine tools and machining centers, machining errors are described in terms of deterministic and random components and analyzed on the bases of their sources, where high machining accuracy and multi-operation under a single setup become major characteristics of manufacturing systems. In machining processes, a resultant dimension may be generated in terms of several relevant dimensions. The dependency of variation among these dimensions is examined and the relationships of locating datum and machining surfaces are analyzed. Variation among linear and angular dimensions are considered. Five basic models of dimension variation relationships are proposed to estimate the machining error, where different formulas of resultant dimension variation are given for different combinations of variation among relevant dimensions. A datum-machining surface relationship graph (DMG) is developed to represent the dependent relationships. A matrix-based reasoning algorithm is designed to search for the shortest path in the DMG. Once the relationship between a specified pair of surfaces is identified, different models of corresponding relationships may be utilized to estimate the possible machining errors which can be used to compare the fixturing accuracy requirement.

Flexible fixturing is a necessary aspect of Flexible Manufacturing Systems (FMS) and Computer-Integrated Manufacturing Systems (CIMS). Modular fixtures are most widely used in industry for job and batch production. Computer-Aided Fixture Design (CAFD) has become a research focus in implementing FMS and CIMS. Fixture configuration design is an important issue in the domain of CAFD. A review of the current research in CAFD indicates that a major problem impeding the automated generation of fixture configurations is the lack of studies on fixture structures. This paper investigates fundamental structures of dowel-pin based modular fixtures and fixturing characteristics of commonly used modular fixture elements. A Modular Fixture Element Assembly Relationship Graph (MFEARG) is designed to represent combination relationships between fixture elements. Based on MFEARG, algorithms are developed to search all suitable fixturing unit candidates and mount them into appropriate positions on a baseplate with interference checking. A prototype system for automated design of dowel-pin modular fixture configurations is presented in this paper. Fixture design examples are given at the end of the paper.

Colonoscopy is the best screening choice for at-risk persons, because it offers prevention through the removal of preneoplastic lesions in addition to early detection. This study aims to report the participation rate of colonoscopy screening and examine its associated factors amongst Chinese first-degree relatives of people with colorectal cancer based on the health belief model (HBM). A cross-sectional study was conducted in Shenzhen, China from March to May 2019. Demographic characteristics, family history, variables derived from the HBM and colonoscopy screening behaviours were measured through online surveys as the independent variables of interest. A total of 186 online surveys were returned, with a final response rate of 57.0%. The participation rate of colonoscopy was 15.6%. Univariate analysis (independent t-test/chi-square test/Fisher test) was applied first to identify the candidate independent variables. Then, multivariate logistic regression was used to examine the association between independent variables and uptake of colonoscopy. Perceived barriers and cues to action were identified as factors associated with undergoing colonoscopy. The participation rate of colonoscopy in the study population was low. Health communication to promote colonoscopy screening for the Chinese at-risk population should include components in reducing barriers to colonoscopy tests, family history information and health professional recommendations on screening. Future studies with large sample size are suggested to examine perceived susceptibility, fatalism and other characteristics considering family history (treatment and outcome of patients) and their potential impacts on cancer screening behaviours for Chinese at-risk populations due to family history.