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Mapping apparel industry 4.0; how industrial Engineer can come forth to handle this management

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Khurram Bahadur

Industry 4.0 – a new business philosophy of the factories in the future which will build up a new concept made up of connected elements: the internet, machines, and people. In such an environment, the artificial intelligence will be set in progress or procedure to transform a set of input by the communication of computers by using large amounts of data. The system consists of autonomous systems, cyber-physical systems, sensors, robots, smart machines, people, and the whole concept from the point of view of business management.  This all will be done while communicating with one another, with humans, and with centralized controllers in real-time as products travel through the production system. Over the industrial Internet of Things, these devices interact with decentralized analytics to enable decision-making and real-time responses such as predicting failure, self-configuration, and adapting to changes.

Industrial production management with mapping apparel industry 4.0:

With the point of view in consumer shift and change, the quality of the product has to be rather higher in demandable and faster to improve with the approach of new functioning in the production process. The operation schedule, strategic planning, maintenance, production efficiency have to be maintained through the integration of data analysis which will be build up from the concept of a multitude of stored data.  The analysis of data has to be included in:

  • Descriptive analysis- what happened
  • Predictive analysis-what should happen
  • Prescriptive analysis – what would like to happen

industry-4-0-logoIn the apparel industry, at first sample approval has to be accepted. The buyer gives a tech pack and gives order with time and chooses the idea about making a prototype sample which has been discussed with the sample development section. In this aspect with a machine vision system, the sample development procedure has to be built up with software and sensors in visual entities like fabric pattern, shade matching, and defect which have been made possible to detect. With the internet of things (IoT), machines can communicate among them. Machines can also communicate with people in real-time to relay important information and take actions accordingly.

According to this view, we need to take proper actions to enter into the global market of sourcing raw materials and in this instance; the entire supply chain is eventually accessible and controllable through the internet. In this aspect, Cyber-Physical Systems will bring a new dimension to the global supply chain indirect transition of raw materials to ‘Smart industry’. So there must be having a team in production management to establish a digital marketing co-coordinator which will give an idea about new ways of understanding as to how customers behave with comparing the non-traditional market.

The comparative analysis trend will give a helpful forecast to monitoring the strategy in future planning of production. The uses of huge automation and big data analytics work has to be formulated with the next steps toward the future for factory production growth to serve the value as ‘smart industry’.

Significance of Industrial Engineer on apparel industry 4.0

The new transformation of some particular operations may be changed, but the length of order cycle, stock exchange by LIFO and FIFO method on stock delivery will be remained by customer relationship and this will bring impact on profit margin ratio.

The apparel industry can breakthrough to adopt new challenges for automation but the opportunity can be built if the factory can run if their finance can stand on breakeven point. In this aspect, necessary implementation has to be applied to the apparel industry in reducing cost with the improvement of work efficiency in these criteria. Industrial Engineer can use some techniques of artificial intelligence tools which will provide necessary implementations:

Analysis of the data storage through cloud computing:

When there are the above data from the Cloud, it can be applied different methods of planning, scheduling, SWOT, TMP, SKK, BSC, failure structure, bottlenecks in the production process, methods of optimization of production processes. Decisions can be made based on data from the production process itself, and not after the end of the production cycle. It means that costs and production cycle times can be minimized. Until now, unit costs of the production process have always been unknown, because of the lack of information within the production.

Optimizing the process of production through Cyber-Physical Systems (CPS):

Physical entities are equipped with technologies such as embedded systems, microprocessors, and sensors that are characterized by being able to collect data by themselves and their environment (Thoben et al., 2017). CPS can process and evaluate this data and communicate with other systems to initiate actions. It is also mentioned that the application of CPS can contribute to the product design phase to production (product life cycle), logistics, and maintenance.

Big data and data analysis:

The industrial engineer has to optimize the complex processes by integrating the social, mathematical, and physical aspects of production systems. In this aspect, some of the main attributes of big data are volume (refers to the quantity); velocity (amount of data generated per unit of time); variety (refers to the heterogeneity and lack of structure), and value (refers to the ability to get information from it). Data analysis term refers to the large amount of structured, semi-structured, and unstructured data created by data sources, which may need too much time and money to be stored and analyzing for value obtainment.

Input data to artificial intelligence (sensor) to remove repetitive task: 

The next aspect that should be mentioned is that the employee is freed from repetitive tasks, then tasks that represent a risky job, hazardous substances, etc. which improves the position of the employee in the I4.0 environment because.  By the setting transformation through the data input; the risk and possibility of injury at work, and on the other hand, employees can be more engaged in creative and innovative work.

Conclusion:

Overall, the reflection of artificial intelligence in the apparel industry will build up stable, reliable supply chains, based on long-term partnerships that are not sustainable in the circumstances of today’s global economy. So, the concept of remote engineering proposed could be used in the aim to enhance competitive advantages that should be an economical experience sharing method for business enterprises. Industrial engineering methods are used to overcome issues in available, common conceptions of how to measure usability.

 

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