Digital Repository

"Predictive model for XYZ apparel manufacturer to foresee on-time delivery deviations due to issues in production process "

Show simple item record

dc.contributor.author Jayaweera, Dasun Lakmin
dc.date.accessioned 2022-03-24T06:37:44Z
dc.date.available 2022-03-24T06:37:44Z
dc.date.issued 2021
dc.identifier.citation "Jayaweera, Dasun Lakmin (2021) Predictive model for XYZ apparel manufacturer to foresee on-time delivery deviations due to issues in production process. BSc. Dissertation Informatics Institute of Technology" en_US
dc.identifier.issn 2019487
dc.identifier.uri http://dlib.iit.ac.lk/xmlui/handle/123456789/1074
dc.description.abstract " The key objective of this research study is to identify the possibility of committed delivery deviations due to process failures within the apparel manufacturing process. Primarily author is focusing on a XYZ company domain which is established in Sri Lankan apparel manufacturing and exporting industry. Being able pre-judge on delivery deviations generates a competitive advantage considering the aggressive nature of the current business environment. Such advantage will allow to utilize business resources of XYZ in the optimum manner and maintain a positive customer relationship as well. As per the investigation done within this research study, author was able to identify key factors which has a direct impact on the planned production end date deviation. Predominantly author’s key focus was to filter out factors which is within the initial phase of the process when the production is initiated and also factors which can be optimized as per the requirement of the manufacturing process. In deriving most influential factors, a comprehensive literature review is done via referring multiple studies from diversified domains. Based on such basis and a study on the apparel manufacturing process, most influential features are identified to evaluate whether delivery commitments can be achieved. Across the study, the hypotheses were developed in relation to these identified variables. Furthermore, a conceptual framework is designed for the identified variables to reflect the relationships and dependencies of each variables and the outcome of it. To progress on the study on XYZ company, PO wise order details are extracted on the variables and the outcomes based on past order placements and trained models using related theories. For the construction of models, a statistical approach was followed which covers the areas of predictive modelling, classification techniques, supervised unsupervised learning etc. Upon which, with the usage of software tools and techniques of R language based R Studio platform, model deployment was completed. Within the study, all identified parameters signifies how an order has processed through the activity sequence of the business to ensure the order is delivered as per the iii committed time period. The variables represents all key corners of the business process with inclusive of quality assurance, sampling, technical, skill allocation, process adherence etc. Ideally, the developed model is adopted to the XYZ business domain entailed with a process driven manufacturing environment which the specified variables are applicable and analyzed to identify possible deviations on delivery commitments. Such ability will enhance the transparency of the business process and foresee to take preventive measures to avoid failures in the critical process activities. In such manner, such solution will strengthen the XYZ company managements’ capability to ensure a healthy customer relationship while avoiding additional cost incurred due to on time delivery failures within the business as well. " en_US
dc.language.iso en en_US
dc.title "Predictive model for XYZ apparel manufacturer to foresee on-time delivery deviations due to issues in production process " en_US
dc.type Thesis en_US


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search


Advanced Search

Browse

My Account