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The purpose of this study is to evaluate the performance of the local insurance in Malaysia for the period 2014-2015. The major challenge in the insurance industry is increasing competition in this market. Besides that, problematic in performance measurement to evaluate performance is another challenge in insurance industry. 24 local insurance companies involved in this study using quantitative method of Data Envelopment Analysis (DEA) output-orientation CCR model. This study utilizes three inputs and three outputs; operating expenses, equity capital and commission as well as net premium, net investment income, and net incurred claim. The secondary data sources were derived from official data of local insurance companies’ annual report respectively. The DEA-Solver-LV version 8 tools were used to analyze the data that have been collected to evaluate the performance of local insurance company. This DEA model allows integration of the performance for the insurance companies and provides management overall performance evaluation. The results showed that there are 8 efficient companies in 2014 and 9 efficient companies in 2015. The average efficiency score in 2014 was increased from 78.9% to 79.1% in 2015. The findings from this study will benefit the insurance associations in Malaysia, management of insurances companies and policy makers.

Value stream mapping (VSM) is one of a lean technique and a preferred tool to visualize and understand a process flow that involves process mapping technique. VSM is drawn as pictures of processes with the purpose of identifying the flow of work, information, as well as understanding the structure of departments. It helps to reduce waste and lead time in delivery service and even support the administration and management. The application of VSM in Malaysia healthcare is still in early stage. The crucial issue concerned is the long waiting time faced by patient. Therefore, the objective of this study is to improve the process flow of patient by reducing lead time and waste. This study focuses on applying VSM in clinic which involve quantitative data collection. The result provides clear evidence in reducing the lead time and waste by using VSM which has been proposed in the future state map.

Additive manufacturing, also known as 3D printing or digital fabrication technology, is a process of accumulating deposited layers to form solid 3D objects from 3D models in digital fi les. 3D printing technology is a fast-emerging technology. Nowadays, 3D printing technology is successfully applied in shaping the globe and producing most of the products used today, from simple plastics to advanced ceramics and metallics. 3D printing technology can print an object layer by layer, by directly depositing the material using computer software, with only just one click. This paper gives an overview of the Critical Success Factors (CSFs) for 3D printing technology in manufacturing fi rms.The literature found in this paper is mainly from Emerald Insight, Science Direct, Google Scholar and Additive Manufacturing. Briefl y, the list of Critical Success Factors can be divided into nine major factors, which are cost, technology, business and support, management and organisation, materials, quality and accuracy, demand, the environment and lastly, research and development.

-Overall Equipment Effectiveness (OEE) is a hierarchy of metrics to measure the production machine performance in manufacturing industry. OEE measurement is inspired by the Total Productive Maintenance (TPM) and used as a key machine performance tool which measures availability, performance and quality rate. This study was conducted in a manufacturing company producing a broad range of packaging products. The main issue found relating to machine productivity was where availability shows a significant decrease since the purchase date.. Thus, data were collected for 12 months from the corrugator's machine and analysed using Microsoft Excel Software to determine the value of the output table, and presented graphically. The results of this study revealed that availability achieved an improvement of 5 per cent over the world standard OEE of 90 per cent, while the machine performance and quality rate each accounted for 10 per cent and 5 per cent decrease in the 'Ideal' value of OEE. Moreover, the comparisons with the 'Ideal' value of OEE were an indication level of total productivity improvement.