Browsing by Author "Burkart, Adrian"

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    Development of a conceptual framework for integrating intelligent-product structures into a flexible manufacturing system
    (Stellenbosch : Stellenbosch University, 2022-11) Burkart, Adrian; Bitsch, Günter; De Kock, Imke; Stellenbosch University. Faculty of Engineering. Dept. of Industrial Engineering.
    ENGLISH ABSTRACT: Product complexity, shorter product life cycles, and short lead times to market challenge the manufacturing industry. Consequently, manufacturers seek to respond with a growing product variety. and new business models to serve the customer’s individual needs. Thus, there is a need for flexible. manufacturing. In particular multi-model production requires enhanced communication and decision-making of the manufacturing resources. Addressing these challenges without IoT technologies will be difficult. Thus, integrating intelligent-product structures is the leading pathway toward a flexible manufacturing system. The industry 4.0 paradigm requires methods for integrating IoT Solutions into manufacturing. These solutions mainly consist of connected, intelligent products to increase flexibility and adaptability in smart factories. However, identifying the requirements and solution scenarios incorporating intelligent products presents a challenge for the manufacturing industry, especially in the SME sector. There are still uncertainties when implementing intelligent-product structures and managing mixed product intelligence structures holistically. This thesis aims twofold: firstly, contextualising flexibility, intelligent products, and their required technologies. Secondly, providing a conceptual framework to analyse the existing manufacturing environment and derive intelligent-product structures. In the context of flexibility, intelligent products only directly influence the four dimensions: Material handling flexibility, Process flexibility, Routing flexibility, and Program flexibility. The systematic literature review provides comprehensive models for defining and classifying intelligent products in manufacturing. A generic product classification regarding its functionalities across the entire product lifecycle is established, and fundamental technologies for each functionality are derived. Thus, the literature review addresses the first part of the research aim. The Intelligent-Product Initiation Decision-Support (IPIDS) framework, as a designed result of the requirement specification, defines, analyses, designs, and executes intelligent products and resources within the context of flexible manufacturing. Methods, tools, and processes are provided to guide the user through the four stages of the IPIDS framework. The first stage of definition assesses the existing infrastructure of the manufacturing by classifying the products and resources according to functionalities. In addition, manufacturing problems are identified and classified. Subsequently, a feasibility study of the identified problems derives the desired solution to manage the manufacturing problem with intelligent products. Stage 3 specifies design requirements based on the target functionalities of the products. Finally, the design requirements are used to develop intelligent products. Thus, the IPIDS framework addresses the second part of the research aim of providing a holistic concept to assess the existing manufacturing environment, identifying value-adding factors through intelligent products, and deriving design and implementation concepts. The evaluation of the IPIDS framework is addressed through a theoretical verification and a prototype implementation in a learning factory. The implementation findings showcase that the IPIDS framework provides applicable, valuable and practicable methods for assessing the manufacturing environment based on the functionalities of the products and resources and deriving implementation concepts for intelligent-product structures. The validation is based on a comprehensive application of the IPIDS framework and statistical analysis, comparing the initial situation with the developed solution. The validity and applicability of the IPIDS framework provide a premise for intelligent-product structures in flexible manufacturing systems.