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Today, Industry 4.0 concerns a rapid advancement in manufacturing technologies which help industries increase their productivity. To adopt Industry 4.0 concept is still visionary by certain lean manufacturers when the communication technologies interfaces are not fully equipped at the production system. Most of the facilities towards digitalization are also expensive and require many specialists in different fields to manage the technologies. Therefore, most data analytics (DA) engineering is cannot be employed broadly for process enhancement by Industry 4.0 environment. However, starting with Internet of Things (IOT) concepts, Andon system with simulation was enhanced to support decision making in lean manufacturing. The aims of this research paper is to develop a decision support system (DSS) framework which intersects between Andon and simulation through IOT concept. A better decision-making information flow are demonstrated in detail. To illustrate the applicability of the DSS, it has been implemented in lean manufacturing for automotive part assembly. The results indicate that the DSS can easily be adopted in digital factories to support in planned and operational activities.search engine platform where they provide various Internet services. Virtualization technology provides cloud computing with flexible extensions, dynamic allocation, resource sharing, and other features. The cloud computing model provides services to the user including software, hardware, platforms, and other IT infrastructure resources as required. The user simply uses resources depending on application needs, relying on on-demand access to computers and storage systems. In manufacturing, the cloud is used as a platform where various production resources and capabilities can be intelligently sensed and connected into the cloud. Then IoT technologies such as sensors or actuators can be used to automatically manage and control these resources so that they can be digitalized for sharing.One of the main goals to set-up a company is to obtain a generous profit. Therefore, to achieve a good profit is by increasing productivity. To manage high productivity, the computing simulation is become more widely to use in the lean production process. Through the simulation, decision-makers are allowing to study the optimal condition for the coming production line in the virtual world before making the change of production line. Simulation models entails oversimplified assumptions and rough approximations to overcome the complexity of manufacturing systems which widen the gap from reality . This has become a new challenge since modern information and communication technologies are a rather complex set of hardware, software and organizational solutions processed with the data (Koscielniak and Puto, 2015). Development of Methodology of Decision Support SystemIn the development stage, firstly, IoT ecosystem involves web-enabled smart devices that use sensors, embedded processors and communication hardware to collect, act and send the data acquired. Through...

<span>Nowadays, the digitalization of the production-based industries is driven by emerging technologies tools. The concept of lean manufacturing (LM) towards Industry 4.0 was developed where data analytics of engineering processes are analyzed and connected to reduce wastes. Many authors discuss about the benefits of extending data analytics as a method to support decision. However, the absence of comprehensive framework on how to embed LM and IT tools has existed as a new challenge. The aim of the research is to initiate a framework of model driven decision support system (MD-DSS) where data simulation and communication technologies are accompanied for manufacturing process improvement. In this research, Overall Equipment Effectiveness (OEE) data was captured through internet networking system and simulate to predict the improvement output. The main information flow route within MD-DSS are demonstrated in detail to show how decision-making process. To illustrate the applicability of the MD-DSS, it has been applied at food industry in Malaysia. The results show that the MD-DSS can easily be adopted in factories facilited with internet network to support decision-making of improvement plan activities.</span>

In this study, the researchers aimed to investigate the awareness of the Malaysian manufacturing industries with regards to the implementation of the Industry 4.0 concept and also determine its levels. Different sectors of the Malaysian manufacturing sector like the Government Link Companies (GLCs), Small and Medium-scale Enterprises (SMEs), and other national or Multinational Corporations (MNCs) were included in this study. The researchers applied a survey-based research methodology and their sample size consisted of 91 Malaysian corporations. The participants in this study comprised of the managers and employees, as company representatives, and they were asked to complete the questionnaire and participate in the interview. The results of the survey showed that around 50.5% of respondents were aware and familiar with the Industry 4.0 regulations. Also, according to the survey results, the awareness regarding the Industry 4.0 regulations was mainly due to the foreign sectors including the multinational corporations like the electrical and electronic industries which contained several advanced assets and increased productivity. These results were very helpful for further research, especially for creating a future framework that could assimilate the ideas related to Industry 4.0 amongst the various other Malaysian industries belonging to the manufacturing sector.

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