Lean Manufacturing in Industry 4.0

Lean Manufacturing in Industry 4.0

Abstract

Industry 4.0 is one of the hotly discussed and searched topics of present day in manufacturing industries and at the same time lean manufacturing is broadly used and considered as an effective tool to improve the operational efficiency and reducing the cost by identifying the non-value added activities in all the processes in an organization. But then, implementing lean in an organization for complex operations faced some hurdles. With technology evolution, the modern world is driven by data and internet of things. With the objective of supporting the organizations to overcome the challenges and hurdles, Industry 4.0 provides new methodologies for managing complex problems and to improve the operational efficiency. Industry 4.0 helps to merge the physical with the digital world and creates an opportunity in making smart factories. Also, examines the link between Industry 4.0 and lean principles and explores whether Industry 4.0 is fit for executing the lean principles. And, demonstrates the theory that Industry 4.0 is undoubtedly fit for implementation of lean manufacturing.

Lean Manufacturing in Industry 4.0

Lean concerns a production system that is oriented on learning of organization through continuous improvement (Mrugalska & Wyrwicka, 2017).               The essential guideline of lean production system depends on removing the eight type of waste. These causes are abridged by transportation, storage, accessibility of processes, unnecessary movements, wait times, overproduction, defects and inefficiency use of employee skills (Leyh, Martin, & Schäffer, 2017). Generally, the successful execution of any administration practice regularly depends on organization qualities. However, it ought to be accentuates that not all associations can or even should apply the same set of practices. The most often revealed practices commonly associated with lean production are: removing bottleneck, cellular manufacturing, continuous improvement programs, cross-functional work force, cycle time reductions, focused factory production, just-in-time, lot size reduction, planning and scheduling strategies, preventive maintenance, process capability measurements, Kanban systems, SMED and total quality management (Mrugalska & Wyrwicka, 2017). The successful implementation of lean principles and tools differs based upon the organization size. These days most modern industries are following lean principles in contrast with that usage rate is low in small scale and medium industries. Industry 4.0 comprises out of innovative chances yet in addition out of parts of an administration vision. The industry 4.0 visions describes previously outlined implementation of smart factory with necessary adjustments of management strategies, investigation into new business models as well as the development of new business process (Wagner, Herrmann, & Thiede, 2017).  The main technology for industry 4.0 is cyber-physical systems (CPS). CPS are the result of a closed loop of sensor based physical process data acquisition combined with software based (cyber) data processing and autonomous actuator based process controlling connected with the internet and its data and services (Wagner et al., 2017).  The application of CPS in a smart factory is called cyber-physical production systems (CPPS). Based on the elements connected data acquisition, data processing, machine to machine communication and human-machine interaction a decentral autonomous production controlling will be possible (Wagner et al., 2017).  For integrating the lean manufacturing and industry 4.0, the reference articles showed terms like lean 4.0, lean manufacturing and lean industry 4.0. From a manufacturing viewpoint, industry 4.0 is understood as the development of insightful work pieces that autonomously organize their ways through a production line. Machine can understand these tracks and convey progressively with the corresponding storage or stockroom. Data is basically used to evaluate and control current procedures. The lean method Just-In-Time (JIT) aims to deliver the right product, at the right time, place and quality in the right quantity for the right costs (Mayr et al., 2018). Automated guided vehicles (AGV), for instance, can transport objects within the material flow automatically. This minimizes human mistakes as well as empty trips. Besides, material is supplied to workstations in accordance to the requirements. In case of obstacles the transportation system will reroute the vehicle to an alternative path (Mayr et al., 2018). Moreover, intelligent totes and smart items likewise seek after self-streamlining. A computerized item memory stores each fundamental assembling parameter. In combination of the movement of materials, it is utilized to explore the AGV productively. This self-association fabricates vigorous coordinates systems for creation. In addition, Auto-ID technology, such as RFID, can be applied to track material in real-time and to localize objects in the value chain precisely. This results in reduced search time as well as improved process transparency. Additionally, part recognition allows the identification of incorrect components. Parts can then be removed, which contributes to the idea of poka-yoke. Moreover, the automated selection of RFID tags enables continuous stock monitoring which eventually results in reduced inventory levels. Besides, it facilitates an automated replenishment process from suppliers (Mayr et al., 2018). The JIT 4.0 method additionally applies big data and data analytics techniques. The opportunity to analyze detailed real-time process information provides insights into parameters, helps to identify trends, and allows to deduce rules for the production system (Mayr et al., 2018).  Furthermore, a continuous material flow is supported by reducing machine down times through predictive maintenance actions. In general, data analysis has the potential to contribute to an improved system performance of the whole supply chain. Overall, JIT 4.0 convinces with higher transparency, shorter lead times and improved flexibility. Apart from this, supply chain actors benefit from a better cooperation and an improved resistance against disturbances (Mayr et al., 2018). New potential outcomes from data and correspondence advances are coordinating with lean creation situations. The paper demonstrates that Industry 4.0 applications can balance out and bolster lean standards. The utilization instance of the digital physical Just-in-Time conveyance application demonstrates a survey capable case of lean procedure upgrades with industry 4.0 advances.

Reference

• Leyh, C., Martin, S., & Schäffer, T. (2017). Industry 4.0 and Lean Production—A matching relationship? An analysis of selected Industry 4.0 models. Paper presented at the 2017 Federated Conference on Computer Science and Information Systems (FedCSIS).
• Mayr, A., Weigelt, M., Kühl, A., Grimm, S., Erll, A., Potzel, M., & Franke, J. J. P. C. (2018). Lean 4.0-A conceptual conjunction of lean management and Industry 4.0. 72, 622-628.
• Mrugalska, B., & Wyrwicka, M. K. J. P. E. (2017). Towards lean production in industry 4.0. 182, 466-473.
• Wagner, T., Herrmann, C., & Thiede, S. J. P. C. (2017). Industry 4.0 impacts on lean production systems. 63, 125-131.