Harnessing Optimal Usage of Data In Manufacturing

Subscribe

- Never miss a story with notifications

- Gain full access to our premium content

- Browse free from up to 5 devices at once

    Media Packs

    Expand Your Reach With Our Customized Solutions Empowering Your Campaigns To Maximize Your Reach & Drive Real Results!

    – Access The Media Pack Now!
    – Book a Conference Call
    – Leave Messiage for us to Get Back

    Related stories

    Smart Features For Manufacturers To Achieve Efficiency

    Accelerating Decarbonization Through Smarter Features for Manufacturers In the push...

    Generative AI: Transforming Manufacturing Operations

    Transforming Manufacturing Operations with Generative AI: A $4 Trillion...

    Resilience And Growth In The U.S. Manufacturing Today

    Strengthening U.S. Manufacturing: Strategies and Trends for Resilience As a...

    Due to the availability when it comes to advanced tech, manufacturers happen to be going ahead and making utmost use of data, which happens to be collected from multiple data sources with the primary objective of throttling efficiency, elevating quality, as well driving innovation. Let us have a look at the transformative effect of data in manufacturing and how it is going about reshaping the sector as a whole.

    The Present Scenario

    It is well to be noted that manufacturers go on to come with massive amounts of data from numerous sources, such as IoT devices, sensors, and also ERP systems. This data happens to provide insights in terms of every aspect as far as the production process is concerned, right from supply chain logistics to machine performance. Considering an average manufacturing site running more than 100 software applications, it is indeed a massive challenge to go ahead and make the data a tad more accessible as well as actionable. As and when this data-driven approach is executed, it brings to the fore innovation and also a level of competitiveness. But the challenge is in efficiently making use of this data value from a blend of technologies by way of numerous execution techniques.

    Advantages of Data Utilization

    Efficiency Enhancements

    Data-driven strategies when it comes to the manufacturing sector enable the manufacturers to make the operations seamless, decrease the waste, and also make full use of allocation of resources. Through analyzing the production data, companies can very well pinpoint the bottlenecks and at the same time execute a solution so as to elevate the throughput.

    Maintenance that’s predictive

    Predictive analytics, which happen to be powered through machine learning algorithms, help the manufacturers to predict system failures. This kind of proactive approach goes on to lessen the downtime, cut the cost associated with maintenance, and also elongate a machinery’s life.

    Control on Quality

    It is worth noting that data analytics go on to play a very critical role when it comes to maintaining top-notch standards. Through tracking the production processes, and that too in real-time, manufacturers can go on to pinpoint anomalies and, at the same time, make sure that the products meet their required specifications, hence altering the defects and even recalls.

    Major Technologies

    IoT

    The IoT devices are the epicenter of data collection in the manufacturing spectrum. Such kinds of connected devices go ahead and offer data in manufacturing that’s real-time on the performance of the machine, conditions of the environment, as well as inventory levels, and thereby help in informed decision-making. IoT sensors can be made use of for varied and many purposes. Below are some of the data points that can be collected by way of IoT sensors-

    Equipment Tracking – Assess real-time performance of the machinery and all its health.

    Maintenance that’s Predictive – Accumulating the IoT sensor data so as to pinpoint any early signs of wear and tear and hence schedule timely repairs if needed.

    Environmental tracking – Assess the temperature, quality of air, and also humidity so as to make sure of the right conditions.

    Tracking the Inventory – Track the stock levels and automate the processes of reordering.

    Consumption of Energy – Monitor and also make utmost energy usage throughout the facilities.

    Tracking of Assets and also Traceability – Tracking the movement as well as condition of goods that are in transit.

    AI & ML

    It is well to be noted that AI, along with machine learning, goes on to offer very productive tools when it comes to predictive analytics as well as automation as far as the manufacturing sector is concerned. These techs help the manufacturers to go ahead and also evaluate datasets that are complex, unearth the patterns, and at the same time optimize the processes so as to attain an ample amount of efficiency. These are certain use cases that can be built by way of using AI as well as ML algorithms-

    Maintenance that is predictive – Forecasting failure of equipment by way of using the sensor data. This enables a reduction in the downtime of the machine.

    Statistical Process Control – SPC happens to be a quality control mechanism so as to automate any sort of defect detection. This aids in the identification of patterns when it comes to process anomalies.

    Optimization of Inventory – Make use of demand forecasting to go ahead and maintain adequate stock levels and, at the same time, decrease the holding costs.

    Optimization of Supply Chain – Enhance the logistic front and decrease any sort of delays.

    Optimization of Process – Elevate the efficiency of production through evaluating the workflow as well as pinpointing the bottlenecks.

    Planning in Terms of Production – Make use of predictive models so as to optimize the scheduling part and also allocation of resources.

    Detection of Anomaly – Pinpoint patterns in operations that look pretty unusual in order to safeguard oneself from any potential challenges.

    Automation as well as Robotics – Executing robots that are intelligent for certain tasks ranging from assembly to packaging.

    Customer Demand Prediction – Forecast the trends in the market along with the needs of the customers so as to keep in sync accordingly with production.

    Big Data Evaluation

    Notably, big data analytics goes on to include processing as well as analysis of large volumes of data so as to extract some actionable insights. By way of leveraging data, manufacturers can go on to have a very deep understanding in terms of trends of the market, preferences of the prospects, and also the functional performance.

    Strategies for Execution

    Integration of Data

    A major hurdle when it comes to utilization of data in manufacturing is integrating data from varied sources. Systems have to be established so as to enable a very seamless flow of data across function lines. The fact is that a unified view when it comes to operations can be brought into place once the data gets integrated from numerous sources. There are certain typical data sources that need to be taken into account, such as

    IoT Devices – Real-time tracking when it comes to equipment performance as well as environmental scenarios.

    Sensors – Data when it comes to temperature, vibration, humidity, as well as other key parameters that depend on the kinds of sensors.

    ERP Systems – Information pertaining to inventory, production planning and also supply chain logistics.

    Manufacturing Execution Systems – Data based on production scheduling, WiP, and also quality control as well as service information.

    SCADA – Supervisory control along with data acquisition and that too concerning process monitoring in real-time.

    CRM – Customer touchpoint data as well as forecasting pertaining to demand.

    Data on Supply Chain – Data coming from suppliers as well as other logistics associates.

    QMS – Data pertaining to quality as well as compliance of the product.

    Cybersecurity

    It is well to be noted that as data in manufacturing goes on to become more valuable, safeguarding it from cyber issues and threats happens to be paramount. Manufacturers have to execute firm cybersecurity steps so as to protect sensitive info and, at the same time, maintain the trust of the stakeholders too.

    Hurdles and Way Out

    There are some of the very typical issues when it comes to harnessing data as far as manufacturing is concerned, such as scalability, gaps in skill, and also data silos.

    Cloud Computing

    The point is that the cloud platforms happen to offer flexible as well as scalable solutions when it comes to storage of data as well as processing. Through migrating to the cloud, manufacturers can get the data accessed in a remote way, hence helping with collaboration and also decision-making that’s real-time.

    Scalability

    Due to a massive growth in data, scalability is a steep concern. Manufacturers happen to require infra that’s scalable and also certain analytical tools in order to manage as well as evaluate efficiently data sets that are expanding.

    Gaps in Skill

    The successful execution when it comes to data-driven strategies needs to have a set of skilled professionals. Due to tech advancement, there happens to be a very progressive need when it comes to professionals who are skilled in the gamut of data in manufacturing and also analytics. The fact is that manufacturers should address the gap in skill through investing across training and also developing experience in terms of data analytics and fields that are related.

    Data Silos

    These happen to challenge the free information flow in an organizational setup. In order to overcome this, manufacturers have to invest in the integrated systems that help with sharing of data as well as partnerships.

    Trends of the Future

    The data future when it comes to manufacturing looks extremely promising due to emerging tech like smart factories and also digital twins gaining immense momentum. Digital twins, which happen to be the digital replicas of physical assets, help the manufacturers to optimize and also simulate the process of production, thereby elevating efficiency and also decreasing the costs.

    In the End

    All said and done, data is indeed revolutionizing the manufacturing sector, thereby offering unmatched opportunities when it comes to growth as well as innovation. Through embracing strategies that are data-driven, manufacturers can elevate effectiveness, enhance quality, and, at the same time, gain a competitive edge in a market that’s changing in no time.

    Latest stories

    Related stories

    Smart Features For Manufacturers To Achieve Efficiency

    Accelerating Decarbonization Through Smarter Features for Manufacturers In the push...

    Generative AI: Transforming Manufacturing Operations

    Transforming Manufacturing Operations with Generative AI: A $4 Trillion...

    Resilience And Growth In The U.S. Manufacturing Today

    Strengthening U.S. Manufacturing: Strategies and Trends for Resilience As a...

    Subscribe

    - Never miss a story with notifications

    - Gain full access to our premium content

    - Browse free from up to 5 devices at once

    Media Packs

    Expand Your Reach With Our Customized Solutions Empowering Your Campaigns To Maximize Your Reach & Drive Real Results!

    – Access The Media Pack Now!
    – Book a Conference Call
    – Leave Messiage for us to Get Back

    Translate »