Industrial IoT: Benefits, Applications, and Challenges Of Wide-Spread IIoT Implementation - 0 views

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  #1 solulever on 06 Jan 23

   

  The last few years have been witnessing the revolution of Industry 4.0 as many manufacturers are taking up digital transformation to level up their factories. According to a survey conducted by Capgemini, 43% of smart factories were taken up in 2017, which rose to 68% in 2022. It was also found that by 2024, discrete manufacturing would eventually lead to smart factories. The investment in smart factories will increase by 40% in the coming 5 years, which means an increase of 1.7 times the annual investment in comparison to the last years.

  
  

  Yet only 14% of the manufacturers agreed on being successful. This suggests that each of the digital manufacturing projects needs better clarity, accuracy, and precision to measure the progress. To build a successful smart factory, laying a strong foundation of analytics is a must. The desired outcomes can be achieved simply by changing the behaviors, that is, being on top of each incident in the plant. This can be attained by making use of metrics and analytics that help reinforce and create ownership of outcomes. Metrics measure the complete production process to suggest improvements, with a strong focus on product lifecycle approach and quality. To make the manufacturing process more efficient and productive, the right metrics need to be selected that focus on team accomplishments and collaboration instead of the success of a siloed department.

  
  

  Some of the key metrics used by manufacturers to plan, pilot and launch digital transformation projects are as follows:

  
  

  
  
  1. Customer Satisfaction Levels- Customer satisfaction rating is measured through regular customer satisfaction audits and is a metric that should be developed to measure the performance of the end-to-end manufacturing process. Manufacturers building smart factories bank on building customer satisfaction metrics and calculating order shipment dates.
  
  
  2. Inventory Turnover- It is the frequency of a particular facility's inventory being consumed to produce a merchandisable product and renewed over a particular period of time. Inventory turns are commonly determined using the "Average Sales by Inventory" factoring for a given accounting period. An alternative way is to divide the cost of goods sold (COGS) by the average inventory for a given accounting period.
  
  
  3. Perfect Order Performance- It is the measure of a production facility’s efficiency in delivering undamaged and accurate orders to customers before or on the delivery due date. It is measured as the (Percent of orders delivered on time) * (Percent of orders complete) * (Percent of orders damage free) * (Percent of orders with accurate documentation) * 100.
  
  
  4. Order Cycle Time- It is the total elapsed time from the point a customer makes an order to the point it is received. Job cycle time shows how collaborative the total production team is. Smart factory pilots use this metric to assess the contribution of inventory management, supply chain, manufacturing, and fulfilment performance.
  
  

  
  

  There are various other metrics which are powerful in enabling a strong and successful smart factory. The real capability of metrics in smart factories is helping manufacturers understand their importance and their contribution to planning, manufacturing, selling, and maintaining products. Analytics form the foundation for keeping smart factories strongly focused on clients and their changing needs. Their true potential is to deliver meaning and purpose to production teams to relentlessly work to improve manufacturing process performance, product quality, and customer satisfaction.

  
  

   

   

  <div class="cArrow"> </div><div class="cContentInner"><p>The last few years have been witnessing the revolution of <a href="https://solulever.com/brabo" rel="nofollow">Industry 4.0</a> as many manufacturers are taking up digital transformation to level up their factories. According to a survey conducted by Capgemini, 43% of smart factories were taken up in 2017, which rose to 68% in 2022. It was also found that by 2024, discrete manufacturing would eventually lead to smart factories. The investment in smart factories will increase by 40% in the coming 5 years, which means an increase of 1.7 times the annual investment in comparison to the last years.</p> <br /> <p>Yet only 14% of the manufacturers agreed on being successful. This suggests that each of the <a href="https://solulever.com/" rel="nofollow">digital manufacturing</a> projects needs better clarity, accuracy, and precision to measure the progress. To build a successful smart factory, laying a strong foundation of analytics is a must. The desired outcomes can be achieved simply by changing the behaviors, that is, being on top of each incident in the plant. This can be attained by making use of metrics and analytics that help reinforce and create ownership of outcomes. Metrics measure the complete production process to suggest improvements, with a strong focus on product lifecycle approach and quality. To make the manufacturing process more efficient and productive, the right metrics need to be selected that focus on team accomplishments and collaboration instead of the success of a siloed department.</p> <br /> <p>Some of the key metrics used by manufacturers to plan, pilot and launch <a href="https://solulever.com/solutions" rel="nofollow">digital transformation</a> projects are as follows:</p> <br /> <ol> <br /> <li><strong>Customer Satisfaction Levels</strong>- Customer satisfaction rating is measured through regular customer satisfaction audits and is a metric that should be developed to measure the performance of the end-to-end manufacturing process. Manufacturers building smart factories bank on building customer satisfaction metrics and calculating order shipment dates.</li> <br /> <li><strong>Inventory Turnover</strong>- It is the frequency of a particular facility's inventory being consumed to produce a merchandisable product and renewed over a particular period of time. Inventory turns are commonly determined using the "Average Sales by Inventory" factoring for a given accounting period. An alternative way is to divide the cost of goods sold (COGS) by the average inventory for a given accounting period.</li> <br /> <li><strong>Perfect Order Performance-</strong> It is the measure of a production facility’s efficiency in delivering undamaged and accurate orders to customers before or on the delivery due date. It is measured as the (Percent of orders delivered on time) * (Percent of orders complete) * (Percent of orders damage free) * (Percent of orders with accurate documentation) * 100.</li> <br /> <li><strong>Order Cycle Time-</strong> It is the total elapsed time from the point a customer makes an order to the point it is received. Job cycle time shows how collaborative the total production team is. Smart factory pilots use this metric to assess the contribution of inventory management, supply chain, manufacturing, and fulfilment performance.</li> <br /> </ol> <br /> <p>There are various other metrics which are powerful in enabling a strong and successful smart factory. The real capability of metrics in smart factories is helping manufacturers understand their importance and their contribution to planning, manufacturing, selling, and maintaining products. Analytics form the foundation for keeping smart factories strongly focused on clients and their changing needs. Their true potential is to deliver meaning and purpose to production teams to relentlessly work to improve manufacturing process performance, product quality, and customer satisfaction.</p> <br /> <p> </p></div>

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