Publication: Short production runs spc monitoring mobile application using modified vmodel and fuzzy quality function deployment
| datacite.subject.fos | oecd::Engineering and technology::Mechanical engineering | |
| dc.contributor.author | Lim Chong Hon | |
| dc.date.accessioned | 2025-05-19T02:43:25Z | |
| dc.date.available | 2025-05-19T02:43:25Z | |
| dc.date.issued | 2023-04-01 | |
| dc.description.abstract | As a result of globalization, today’s marketplace is fiercely competitive. Catering to consumers’ frequently changing tastes, many manufacturing sectors today embrace customization to provide a greater product variety. In light of this, most of them migrated their existing mass-production model into a short production runs model. This research develops a mobile application (app) for online statistical process control (SPC) monitoring for short production runs. The mobile app adopts the Deviation from Nominal (DNOM) method and generates Shewhart control charts to monitor the measured production variables remotely. Process capability examines the process consistency over time, and Nelson rules determine out-of-control variables. The research methodology applies a modified V-model software development approach, integrating a 2-stage Fuzzy Quality Function Deployment (FQFD). The V-model aligns development activities to the design requirements. FQFD solicits and decomposes user requirements into design requirements. The methodology was demonstrated through the development of an online SPC monitoring app. In the demonstration, FQFD structurally related user requirements, system requirements and design strategies along the Vmodel’s verification phases. Additionally, the validation phases used the test plans created during the verification phases to detect and correct programming errors. In the final validation stage, the focus group agreed that the mobile app met all the user requirements that were requested. From the results of the acceptance test questionnaire, of the nine questions pertaining to the fulfilment of the mobile app requirements, all come with a score of 90% above except the case of using SMS as an effective alert which scored a 60%.The conceived app based SPC monitoring system comprises of a cloud database, mobile internet network, and an online SPC monitoring mobile app built using the MIT App Inventor 2 platform and Google Workspace. Simulated data from a flywheel fabrication case study is used to validate the app’s functionality. This study adds to the methodology’s novelty by proposing and demonstrating the integration of the FQFD and V-model into the development of mobile applications. | |
| dc.identifier.uri | https://erepo.usm.my/handle/123456789/21684 | |
| dc.language.iso | en | |
| dc.title | Short production runs spc monitoring mobile application using modified vmodel and fuzzy quality function deployment | |
| dc.type | Resource Types::text::thesis::master thesis | |
| dspace.entity.type | Publication | |
| oairecerif.author.affiliation | Universiti Sains Malaysia |