Kenneth Kagoiya

ABSTRACT

Industrial development is key to advancement of a country and a major component of GDP contribution to countries having stable and progressive economics. Currently in Kenya manufacturing contributes only about 9%. For advancement and support of other manufacturing sectors like vehicles and material handling systems, machinery and industrial equipment system, medical equipment and systems, electronic manufacturing needs to be in place so as to strengthen the supply chain in these sectors of manufacturing. Electronic and Electrical manufacturing can be categorized in four levels which are semiconductor components, electronic device and circuit modules sub systems for consumer electronics, broadcasting, industrial automation, medical systems and final complete system.

There exist drawbacks and difficulties that hider faster growth in terms of advancement in technology, throughput, numbers, categories, GDP contributions, some of which are limited information on what is already in existence market, regulatory needs, lacks of consolidation and harmonization of technical personnel, lack of financial incentive (market appeal) or potential return of investment, limited ability to make necessary partnerships which will also be addressed in this framework

The proposed framework envisages a system that includes all the categories rationalized appropriately to improve operational efficiency business through put, market mix, optimum architecture of the process. A proposed architecture of the system includes an electronic industrial park with categories one and two and another with category three devices and finally complete industrial system located using a scientific method. The framework has an overall objectives of achieving comprehensive and holistic measures of performances across diverse activities hence appropriate tools and methods identification

Actionable strategy for partnerships in terms of venture capital partners, technology partners and board of management. Reliability systems for functional, requirements, integration of operations tasks and information and communication subsystem.

The expected outcomes of framework are to facilitate performance management, continuous learning and improved decision making by providing relevant, comprehensive timely information to improve on operational efficiency of Setting up manufacturing plants, Personnel recruitment and training, Procurement of equipment, linkages with venture capital partners, decision process of product mix. This will also ensure there are flexible but category suitable guidelines on putting in place effective organization structure and actualizing cost effective and reliable Supply chain system for optimum inventory management

Keywords: Learning Analytics Dashboard, Machine Learning, Adaptive eLearning, Cognitive Load Theory