Rosmaini Ahmad

Bio: Rosmaini Ahmad is an academic researcher from Universiti Malaysia Perlis. The author has contributed to research in topics: Preventive maintenance & Predictive maintenance. The author has an hindex of 8, co-authored 29 publications receiving 783 citations. Previous affiliations of Rosmaini Ahmad include Universiti Sains Malaysia Engineering Campus & Universiti Sains Malaysia.

A review of condition-based maintenance decision-making

Abstract: Condition-based maintenance (CBM) has been a research topic since 1975. It has been introduced as an alternative approach to enhance the effectiveness of preventive maintenance strategy. Currently, CBM research is growing rapidly. Compared with the traditional time-based maintenance approach, CBM application is more beneficial and realistic. With CBM, better maintenance decisions can be made to avoid or minimise unnecessary maintenance costs. This paper attempts to explore how exactly CBM decision-making is conducted, with the methods of decision-making classified into current-condition-evaluation-based and future-condition-prediction-based. This paper systematically reviews the applications of these methods by focusing on the techniques used, as well as on case studies. It concludes with findings based on the academic and industrial perspectives. (Received 10 July 2010; Revised 9 November 2010; Accepted 24 February 2011)

Maintenance management decision model for preventive maintenance strategy on production equipment

Abstract: In industries, Preventive Maintenance (PM) is not a new practice to minimise the sudden breakdown of production machine. PM will be performed at predetermine intervals to provide a balance between failure cost and component utilisation (aging). However, most of PM interval is based on experience or original equipment manufacturer (OEM) recommendations. Consequently, the benefits from PM are not fully obtained because the current machine state is not considered. The aim of this paper is to propose a maintenance management decision model for PM application. The main objective of the model is to revise the PM interval based on current machine state. The proposed model provides step-by-step procedure from data identification, classification, evaluation until determination of the revised PM interval.

Changeover process improvement based on modified SMED method and other process improvement tools application: an improvement project of 5-axis CNC machine operation in advanced composite manufacturing industry

Abstract: This paper shares a real industry experience for an improvement project of the changeover process through a conventional Single-Minute Exchange Die (SMED) method and other process improvement application tools. This project focuses on the changeover activities for one of the advanced composite manufacturing processes, called trimming process that involves 5-axis CNC machine operation. The cause and effect and five whys analysis techniques and some steps of conventional SMED are applied in this improvement project. Four standard strategies and priorities sequence are introduced for an extension step of conventional SMED. The conceptual decision model is then proposed to present the systematic improvement process carried out in this project. Four specific solutions from the selected strategies are then recommended to be implemented. The current implementation results show that the total changeover time is reduced to 44% and internal type activities time is reduced to 48%. The paper discusses some key success factors and future recommendations of the current project.

Wind Turbine Condition Monitoring: State-of-the-Art Review, New Trends, and Future Challenges

Abstract: As the demand for wind energy continues to grow at exponential rates, reducing operation and maintenance (OM) costs and improving reliability have become top priorities in wind turbine (WT) maintenance strategies. In addition to the development of more highly evolved WT designs intended to improve availability, the application of reliable and cost-effective condition-monitoring (CM) techniques offers an efficient approach to achieve this goal. This paper provides a general review and classification of wind turbine condition monitoring (WTCM) methods and techniques with a focus on trends and future challenges. After highlighting the relevant CM, diagnosis, and maintenance analysis, this work outlines the relationship between these concepts and related theories, and examines new trends and future challenges in the WTCM industry. Interesting insights from this research are used to point out strengths and weaknesses in today’s WTCM industry and define research priorities needed for the industry to meet the challenges in wind industry technological evolution and market growth.

Prognostics and Health Management: A Review on Data Driven Approaches

Abstract: Prognostics and health management (PHM) is a framework that offers comprehensive yet individualized solutions for managing system health. In recent years, PHM has emerged as an essential approach for achieving competitive advantages in the global market by improving reliability, maintainability, safety, and affordability. Concepts and components in PHM have been developed separately in many areas such as mechanical engineering, electrical engineering, and statistical science, under varied names. In this paper, we provide a concise review of mainstream methods in major aspects of the PHM framework, including the updated research from both statistical science and engineering, with a focus on data-driven approaches. Real world examples have been provided to illustrate the implementation of PHM in practice.