scholarly journals Work in Progress: Educational Uses of an Intelligent System to Teach Construction Processes – A Case Study of the Giant Wild Goose Pagoda

2020 ◽  
Author(s):  
Fei Yang ◽  
Michael Parke ◽  
Fabian Tan ◽  
Adrian Tan ◽  
Shilun Hao
Keyword(s):  
Intelligent System ◽  
Work In Progress ◽  
Wild Goose

Modelling and Designing of IoT Systems Using UML Diagrams

2019 ◽  
pp. 36-61
Author(s):  
K. Sridhar Patnaik ◽  
Itu Snigdh
Keyword(s):  
Software Engineering ◽  
Design Patterns ◽  
Architectural Design ◽  
Intelligent System ◽  
Patient Health ◽  
Systematic Development ◽  
Uml Diagrams ◽  
Robotic Devices ◽  
Remote Patient

Despite the rapid growth in IoT research, a general principled software engineering approach for the systematic development of IoT systems and applications is still missing. Software engineering as a discipline provides the necessary platform to carry on the underlying design, coding, implementation, as well as maintenance of such systems. UML diagrams present a visually comprehensible outlay of the construction of IoT systems. The chapter covers the modelling of IoT systems using UML diagrams. Starting with the architectural design of any IoT system to behavioral aspects is covered in this chapter using a case study of IoT-based remote patient health monitoring system. The diagrams shown in this chapter are the sample diagrams for understanding IoT-based complex systems. The chapter focuses on the work carried out by Franco Zambonelli in context of developing abstract model of an IoT system using software engineering concepts. The chapter also focus on the pioneer work carried by J. F. Peters in intelligent system design patterns for robotic devices using pattern classification.

scholarly journals Work-in-Progress Inventory Control Case Study in Lean Management

2018 ◽  
Vol 7 (3.4) ◽  
pp. 181
Author(s):  
Hong Wai Tan ◽  
Khairur Rijal Jamaludin ◽  
H S Hamzah
Keyword(s):  
Inventory Control ◽  
Capacity Allocation ◽  
Raw Material ◽  
Value Stream Mapping ◽  
Production Operation ◽  
Lean Management ◽  
Work In Progress ◽  
Current Production ◽  
Wip Inventory

Increasing the rate of converting raw material into finished product and delivering it on time is a main driver for each manufacturing industry to achieve continuous improvement in its business operation.  This case study demonstrates the improvement of the work-in-progress inventory in a non-lean company seeking to adopt lean management.  Introducing the value stream mapping (VSM) lean technique to identify the waste in the current production operation. A selection of lean tools such as Kanban card, supermarket racking and one-piece flow are applied to control and monitor the WIP inventory after justification of the factors (process cycle time, production facilities layout and facilities capacity allocation) that influence the change from the current production operation situation.The construction of the current VSM had identified the major waste in WIP inventory handling in the final fabrication process.  The fluctuation of WIP inventory has been resolved by the implementation of supermarket racking; therefore, an improvement base for WIP inventory control has been established.  Throughout this study, the lean management concept had been fostered into the production floor team and will continue developing to the organization. 

scholarly journals Intelligent system for non-technical losses management in residential users of the electricity sector

2018 ◽  
Vol 38 (2) ◽  
pp. 52-60 ◽  
Author(s):  
Miguel Uparela Cantillo ◽  
Ruben González ◽  
Jamer Jiménez Mares ◽  
Christian Quintero Monroy
Keyword(s):  
Intelligent Systems ◽  
Intelligent System ◽  
Demand Forecasting ◽  
Electricity Sector ◽  
Caribbean Region ◽  
Self Organizing Maps ◽  
Detection Rates ◽  
Distribution Company

The identification of irregular users is an important assignment in the recovery of energy in the distribution sector. This analysis requires low error levels to minimize non-technical electrical losses in power grid. However, the detection of fraudulent users who have billing does not present a generalized methodology. This issue is complex and varies according to the case study. This paper presents a novel methodology to identify residential fraudulent users by using intelligent systems. The proposed intelligent system consists of three fundamental modules. The first module performs the classification of users with similar power consumption curves using self-organizing maps and genetic algorithms. The second module allows carrying out the monthly electricity demand forecasting through of recursive adjustment of ARIMA models. The third module performs the detection of fraudulent users through an artificial neural network for pattern recognition. For the design and validation of the proposed intelligent system, several tests were performed in each developed module. The database used for the design and evaluation of the modules was constructed with data supplied by the energy distribution company of the Colombian Caribbean Region. The results obtained by the proposed intelligent system show a better performance versus the detection rates obtained by the company.

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