Improved decision making in lean manufacturing using simulation-based approach

Mohamad

2020

IJEECS

<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>

Section: : Simulation and Decision Makersmentioning

confidence: 99%

Enhancement of overall equipment effectiveness (OEE) data by using simulation as decision making tools for line balancing

Mohamad

2020

IJEECS

“…Few of these data are employed just for tracking. Apart from that, the management group is not able to analyze accurately the impact of process variables on lean to establish communication and decision making (Mohamad et al, 2017). Production facing problems without establishing a proper communication interconnection vertically where data is analyzing in real time is not ready.…”

Section: Introductionmentioning

confidence: 99%

Internet of things and simulation approach for decision support system in lean manufacturing

Ito

Mohamad

et al. 2020

JAMDSM

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...

“…According to researcher based on literature review [8][9][10], simulation can be defined as an approach to understand or study the behavior of the system (within the limits imposed Enhancement of Time-Driven Activity-Based Costing (TDABC) by using Simulation in Manufacturing Process towards Industry 4.0 by a set of criteria), by creating a model for the actual system and carry out experiments with the said model of an operating system. A simulation model is a cost-saving tool to explore different solutions for a real system that does not require an actual change in the real system [11]. Therefore, users can experiment 'what if' conditions to observe the changes in the system [12].…”

Section: A Simulation Studymentioning

confidence: 99%

Enhancement of Time-Driven Activity–Based Costing (TDABC) by using Simulation in Manufacturing Process towards Industry 4.0

Rahman¹,

Mohamad²,

Rahman³

2019

IJITEE

Self Cite

The new industrial revolution brings changes to organizations that will need to adapt their system to sustain their business in a highly competitive market. In term of costing, most manufacturers continuously working towards reducing production costs by focusing on activities process improvement and resources as a cost driver. One of the current problems faced by most manufacturers that adopted Time-Driven Activity-Based Costing (TDABC) is lack of combined used of simulation as a tool for validation. Conventional technique also caused users estimated incorrect variables consideration to the costing system. The purpose of this paper is to provide a system for managers or decision makers to analyze results which can significantly reduce production costs by eliminating unnecessary resources with the aid of a simulation model. Simulation was proposed as new approach to determine the optimum results based on the given scenarios. An analysis on how the framework was implemented at an automotive manufacturing company was illustrated the enhancement of TDABC by using simulation. Results of conventional method using Activity Based Costing (ABC) was compared with TDABC where existing production layouts and parameters were maintained. Simulation model was created based on current situation and the results were compared to the old method. The results indicated that simulation can easily be adapted to support the planned and operational TDABC activities. Towards industry 4.0 it was proven that simulation is one of the key technologies in the new industrial revolution. Besides that, TDABC methodology in this research is more accurate and faster, by means of an enhanced decision-making process and supported organization manufacturing system.