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

Abstract

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...

Linking data science to lean production: a model to support lean practices

“…In particular, the findings of this study agree with previous research on the use of DS in support of LP practices that considered the 'production planning and control' LP bundle (e.g. Stojanovic et al 2016;Deuse et al 2018;Kutschenreiter-Praszkiewicz 2018;Mayr et al 2018;Abd Rahman et al 2020;Ito et al 2020;Sarkar et al 2020;Shahin et al 2020;Valamede and Akkari 2020). However, differently from previous research, the results of this research demonstrate also that the application of the identified set of techniques and tools is not limited to the 'production planning and control' bundle but can potentially support all the LP bundles.…”

“…A narrow range of studies proposed or presented practical applications of DS to specific LP practices. Ito et al (2020) adopt simulation as a data analytics tool applied to field data in a real-time Andon system, supporting 'visual management of production control'. Abd apply simulation as a data analytics tool to generate overall equipment effectiveness (OEE) values as the 'feedback on performance metrics practice' of a production line.…”

Industry 4.0 Application in Lean Manufacturing – A Systematic Review

“…IoT (Internet of Things) technologies such as RFID (Radio Frequency Identification) and LPWAN (Low Power Wide Area Network) are utilised to enhance digital traceability and to provide real-time information which can be effectively applied in Lean Manufacturing to identify and eliminate the waste [10][11]. IoT has also been used in integrating machines in the shop floor and also to connect to the machines with Andon systems to enhance the decision support system for process improvement [12][13]. IoT has also been applied to transform the traditional JIT (Just-In-Time) into dynamic JIT, which successfully addresses the challenges of traditional JIT by integrating modules integrated with IoT technologies into the Manufacturing Execution System (MES) [14].…”

Lean Manual Assembly 4.0: A Systematic Review

“…Malik and Bilberg proposed a method for assigning tasks to robots or people in Human-Robot Collaborative (HRC) assembly, based on the physical properties of the components, HRC safety, and the dynamics of the HRC environment such as part presentation and feeding [184]. The IoT and simulation could be used to support expert-less decision making, in a similar way to the classic Andon tool does [185]. In any case, systems integration will be needed to ensure that Lean manufacturing systems meet the Industry 4.0 requirements [186].…”