计算机科学
顺从(心理学)
质量(理念)
医疗器械
数据收集
智能制造
质量管理体系
概念框架
概念模型
过程管理
数据质量
风险分析(工程)
管理制度
工程管理
知识管理
质量管理
数据科学
数据库
制造工程
运营管理
业务
哲学
心理学
数学
公制(单位)
经济
生物医学工程
工程类
认识论
统计
社会心理学
医学
作者
Puneeth S. Kannaraya,Manish Arora,Amaresh Chakrabarti
标识
DOI:10.1016/j.procs.2025.01.218
摘要
The medical device manufacturing industry is driven by stringent regulatory compliances and faces challenges in implementing quality management systems. One such challenge is the preparation of the paper-based documentation of all the documents as evidence for certification audits. With the advent of Industry 4.0, the increasing amount of data from the shop floor, with variety and veracity, poses additional challenges to the organization. Various technological interventions have made quality systems suffer from categorizing the incoming data and presenting it in suitable formats. A smart manufacturing conceptual framework with elements of intelligent manufacturing, quality control and smart manufacturing has been developed and proposed. The activities and outcomes of the framework enable the organization to capture data from the shop floor according to the various entities. The TOPSIS decision modeling technique is used to perform the structural validation of the framework. The TOPSIS scores reveal the influence of the framework compared to a conventional process. A statistical test was also performed to emphasize the claim.
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