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Title: Modelling commercial process in ship repair & conversion using artificial neural networks
Author: Sinha, Ashutosh
ISNI:       0000 0004 2719 8168
Awarding Body: University of Newcastle Upon Tyne
Current Institution: University of Newcastle upon Tyne
Date of Award: 2011
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Abstract This thesis discusses the development of a simulation model using artificial neural networks to model and predict the outcome of commercial process at a Shiprepair Conversion yard. Based on the data collected from across the A&P group a simulation model of the commercial process was developed. It was considered that contrary to the popular belief of securing one in five enquires as a potential contract the model can predict the probability of the outcome of a contract. The aim of the simulation is to ultimately develop a decision making tool for the ship repair industry which could help predict the outcome of the an enquiry based on certain parameters, hence reducing the estimating time and giving yards an advantage over their competitors. The research work looks into the estimation and management of Shiprepair and conversion processes, identifies the key stakeholders in the process and looks at the inherent risks of outdated technologies. The development of an intelligent supply chain management will enhance the yards product ability, help reduce the over heads and decrease the tendering process for the total repair. The challenges of assembling and deploying integrated supply chain are not unique to the Shiprepair industry. Increasing international pressures are motivating all industrial corporations continuously to reduce cycle times, manufacturing & administrative costs and to increase productivity. In addition, to improve internal production efficiency shipyards are turning to external factors such as subcontractors and suppliers. Improving supply chain management can help yards better understand their production enterprises and these insights can be used to optimize processes and facilities. A key element to improve the efficiency of ship repair supply chain is to improve the integration of, organizations operating within a supply chain. Describing Shiprepair in a nutshell it would right to say that: - 8 - --------_1 "There are known knowns. There are things we know that we know. There are known unknowns. That is to say, there are things that we now know we don't know. But there are also unknown unknowns. There are things we do not know we don't know" 1 and Shiprepair is full of unknown unknowns, the thesis attempts to identify a few.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available