#OEE Trends

[ks-group-zirakpur]

OEE Tracking Solutions vs. Traditional Monitoring Systems: What’s the Difference?

In the dynamic manufacturing world, tracking equipment performance to optimise productivity and minimise downtime is key. Although traditional monitoring systems can be found in the industry, modern OEE (Overall Equipment Effectiveness) tracking solutions are increasingly becoming the go-to for digital transformation. So, what is the difference, and which one is better suited for today's manufacturing challenges?

What Are Traditional Monitoring Systems?

Traditional monitoring systems mainly focus on simple performance reporting through hand-writing logbooks, standalone counters, or spreadsheets. The systems need more information regarding equipment performance, and data retrieval frequently requires human intervention before analysis. These systems were adequate for the less complex manufacturing operations but needed help dealing with the complexity of a modern operation.

For instance, the traditional method may track machine uptime but is not usually effective in giving actionable insights on determinants like performance efficiency or product quality. Their typical manual nature makes them more prone to errors and inefficiencies, so manufacturers become reactive rather than proactive in these matters.

Understanding OEE Tracking Solutions

Contrarily, OEE tracking solutions are designed especially for proper equipment monitoring. There are three fundamental factors assessed.

Availability: Number of hours a machine is online compared to scheduled time.

Performance: Whether equipment is working to its capacity or actual speed.

Quality: Percentage of products meeting the requirements specified without defect or rework.

These systems utilise real-time data accrual, advanced analytics, and automation to consistently view equipment productivity. OEE solutions can easily be integrated with the deployment of today's leading-edge technologies like MES (Manufacturing Execution Systems) and IoT (Internet of Things), which allows manufacturers to track and improve equipment performance in real-time.

Key Differences Between Traditional Monitoring Systems and OEE Tracking Solutions

1. Gathering of Data

Traditional systems rely on manual data entry, making the process time-intensive and error-prone. In contrast, OEE solutions automate data collection through sensors and software, ensuring accuracy and enabling real-time updates. It is an excellent tool for engineering process automation in terms of data collection.

2. Observations and Analysis

Traditional monitoring provides basic metrics that often require manual interpretation. OEE tracking systems go further, delivering detailed analytics and visualisations that help identify trends, inefficiencies, and potential failure points.

3. Interoperability with Modern Systems

Traditional systems operate like unconnected tools, with little or no ability to connect with other systems. OEE solutions, on the other hand, are simply integrated with ERP/MES and IoT platforms, thus setting a seamless manufacturing management ecosystem.

4. Scalability 

Traditional systems need help scaling in complex, multi-site operations. In contrast, OEE solutions are designed for scalability, making them particularly well-suited to manufacturers with many production lines or locations.

5. The Actionability of Data

Traditional systems often see insights too late, then back maintenance. The OEE solution helps make proactive decisions by implementing predictive analytics that help prevent downtime before it occurs.

Benefits of Upgrading to OEE Tracking Solutions

This investment in OEE tracking solutions helps manufacturers take numerous advantages:

Better Productivity: Real-time insights minimise downtime and optimise workflows.

Correct Choice Making: Analytics results in better resource utilisation and strategic planning.

Higher ROI: More efficiency and less waste represent higher ROI. 

Overall Monitoring: The OEE tools measure all these parameters, ensuring balanced performance improvement across all equipment through engineering process automation. 

Challenges and Considerations 

Transitions to OEE solutions are also characterised by certain problems, such as the initial costs and the requirement of employee training; besides, compatibility with existing equipment may require extra investment. Despite this, most of these barriers are often overtaken by benefits that endure, such as efficiency building up and profits increasing. 

Traditional monitoring systems fulfilled their roles in earlier periods when they were less complex. However, they need to cater to the demands of today's fast-paced manufacturing places. The real-time functionality and analytics-performing OEE tracking solutions allow manufacturers to manage the equipment in a more holistic and foretelling manner. OEE tracking systems are necessary for manufacturers to embrace Industry 4.0 standards to compete.

[team-ombrulla]

How to Improve Overall Equipment Effectiveness (OEE) in Asset Performance Management

Introduction

Overall Equipment Effectiveness (OEE) is a key metric for assessing how efficiently equipment is used within an organization. Improving OEE can significantly impact productivity and profitability. When combined with Asset Performance Management (APM), which includes the use of advanced technologies like predictive maintenance, organizations can achieve optimal equipment utilization. This article provides practical strategies for enhancing OEE using APM principles.

Strategies to Improve OEE with APM

Integrate Predictive Maintenance APM software offers predictive maintenance capabilities that use real-time data to anticipate potential equipment failures. By addressing issues before they result in downtime, equipment availability is maximized, boosting the OEE score.

Leverage Real-Time Monitoring APM software provides continuous monitoring of asset performance, enabling teams to respond swiftly to anomalies. This proactive approach enhances performance and prevents issues that could lower the OEE score.

Optimize Maintenance Schedules Traditional maintenance schedules can result in unnecessary downtime. APM software uses data analytics to suggest maintenance only when needed, ensuring equipment remains operational for as long as possible without compromising performance.

Utilize Data-Driven Insights APM solutions collect extensive data that can be analyzed to find trends, identify inefficiencies, and improve processes. Insights gained from data analytics can help refine operations to achieve better performance and product quality.

Employee Training and Engagement Even with advanced APM systems in place, employee training is essential for effective use. Ensuring staff are well-versed in interpreting data and making informed decisions can significantly contribute to higher overall equipment effectiveness.

Conclusion Improving OEE within an organization requires a combination of strategic approaches and advanced tools like APM software. By leveraging predictive maintenance, real-time monitoring, and data-driven insights, organizations can enhance equipment efficiency, reduce downtime, and achieve sustainable growth. Adopting these strategies ensures that assets operate at peak performance, benefiting overall operations and contributing to long-term success.

[eaglecmms]

The Role of Computerized Maintenance Management Systems in Streamlining Industrial Operations

In today’s hyper-competitive business ecosystem, even a minute of downtime translates to lost productivity, increased costs, and potential safety hazards. To streamline their operations and stay competitive, industries are increasingly turning to Computerized Maintenance Management Systems (CMMS). Let's delve into how CMMS software plays a pivotal role in optimizing maintenance processes and enhancing productivity in industrial settings.

Understanding Computerized Maintenance Management Systems

Computerized Maintenance Management Systems are powerful tools designed to facilitate the planning, execution, and tracking of maintenance activities within an industrial set up. Unlike traditional paper-based or spreadsheet methods, CMMS software centralizes maintenance data, providing real-time insights into equipment health, work orders, and resource allocation.

Preventive maintenance: Proactive approach to equipment reliability

One of the key functionalities of CMMS solutions lies in their ability to implement preventive maintenance schedules. By scheduling routine inspections, servicing, and repairs based on equipment usage or predefined intervals, industrial facilities can proactively address potential issues before they escalate into costly breakdowns.

For instance, in a manufacturing plant, CMMS software can automatically generate work orders for regular equipment checks, lubrication, or calibration. This proactive approach not only minimizes unplanned downtime but also extends the lifespan of critical assets, ultimately reducing maintenance costs.

Asset management: Optimizing resource utilization

Industrial facilities house a multitude of assets, ranging from machinery and vehicles to tools and infrastructure. Managing these assets efficiently is essential for maximizing productivity and minimizing operational disruptions. Asset maintenance management software provides a centralized repository for asset information, including maintenance history, specifications, and warranty details.

With cutting-edge CMMS solutions on hand, maintenance teams can easily track the performance and status of each asset, enabling informed decision-making regarding repairs, replacements, or upgrades. Furthermore, predictive maintenance features within advanced CMMS platforms leverage data analytics and machine learning algorithms to forecast equipment failures, allowing organizations to take pre-emptive actions to avoid downtime.

Work order management: Streamlining maintenance processes

In a bustling industrial environment, managing work orders manually can be a logistical nightmare. CMMS software automates the entire work order lifecycle, from creation and assignment to completion and documentation. Maintenance technicians can access work orders via mobile devices, allowing them to view task details, record findings, and update job status in real-time.

Moreover, CMMS streamlines communication between maintenance teams, supervisors, and other stakeholders by providing a centralized platform for collaboration. This fosters transparency and accountability, ensuring that maintenance tasks are executed promptly and efficiently.

Data-driven decision making: Insights for continuous improvement

In the digital age, data is king. CMMS software empowers industrial facilities with actionable insights derived from maintenance data. By analyzing key performance indicators such as Mean Time Between Failures (MTBF), Mean Time to Repair (MTTR), and Overall Equipment Effectiveness (OEE), organizations can identify trends, pinpoint areas for improvement, and optimize maintenance strategies.

For example, by analyzing maintenance data, a chemical plant may discover that a particular pump consistently fails after a certain number of operating hours. Armed with this knowledge, the plant can adjust its preventive maintenance schedule or invest in upgrading the pump to a more robust model, thereby minimizing disruptions to production.

Eagle CMMS – Powering your plants with innovative maintenance management systems Computerized Maintenance Management Systems stand as the linchpin for operational excellence in industrial settings, driving efficiency, reliability, and competitiveness. By embracing CMMS solutions like Eagle CMMS, organizations embark on a transformative journey from reactive to proactive maintenance, empowered to navigate the complexities of modern industry with confidence.

Eagle CMMS transcends mere software; it emerges as a strategic ally committed to maximizing maintenance efficiency and reliability. Through proactive maintenance strategies, optimized asset management, and streamlined work order processes, Eagle CMMS empowers businesses to minimize downtime, reduce costs, and maintain a competitive edge in today's fast-paced market.

Moreover, our dedication extends beyond software provision. We prioritize comprehensive training, unwavering support, and continuous enhancements to ensure that Eagle CMMS remains at the forefront of industry innovation. With Eagle CMMS as your trusted partner, you're not just investing in software; you're fortifying your business for sustained success and resilience in the ever-evolving landscape of industry.

As technology continues to evolve, CMMS software like Eagle CMMS will remain an indispensable tool for achieving operational excellence and plant wellness. Choose Eagle CMMS and embark on a path toward operational excellence, where every step is guided by innovation, reliability, and commitment to your success.

To learn more visit our website or sign up for a free 14-day trial.

[biggolderp]

เข้าร่วมสัมมนาออนไลน์ กับ สถาบัน ICTI ร่วมกับ TrueBusiness เชิญรับฟัง

➡️หัวข้อ "Preventive Maintenance for Smart Factory

ลดความเสี่ยง เพิ่มประสิทธิภาพการผลิต ด้วยระบบตรวจจับความผิดปกติของเครื่องจักรอัจฉริยะ (Machine Health Solution)"

ในวันพฤหัสบดีที่ 14 มีนาคม 2567

พบกับ

-Global Trend for Industrial Transformation Framework การทำ Industrial Transformation เริ่มต้นอย่างไร

เพื่อเข้าสู่การเป็น Data-driven -Organization Machine Health solution โซลูชั่นที่ดีที่สุดในการเพิ่ม Availability

และเพิ่ม OEE ได้จริง

-Digital Solutions ที่ตอบโจทย์การซ่อมบำรุงให้เป็น Smart Maintenance

-Use cases ผู้ใช้งานจริงในภาคอุตสาหกรรมโดยเฉพาะ

สิ่งที่จะได้รับ:

-ลดความสูญเสียจาก Unplanned Shutdown ของเครื่องจักร

-Real Time Monitoring และระบบ��จ้งเตือนทันที เมื่อเครื่องจักรเกิดปัญหา

-ทดแทนการซ่อมบำรุงแบบตามระยะ ลดเวลาการติดตามและวิเคราะห์ข้อมูล

-เปลี่ยนการซ่อมบำรุงจาก Traditional operation เป็น smart operation

-มีข้อมูลในรูปแบบ digital สามารถนำมาวิเคราะห์ต่อได้ทันที เพิ่มประสิทธิภาพในการตัดสินใจ

-มีแนวทางการจัดการซ่อมบำรุงรักษาเชิงป้องกัน เพื่อตอบโจทย์ Industry 4.0

เพิ่มประสิทธิภาพการผลิตโดยรวม (OEE)

-มี Solution ที่เหมาะสม สำหรับการพัฒนา Preventive Maintenance ในโรงงาน

งานนี้เหมาะสำหรับ

-องค์กรในภาคการผลิตที่ต้องการเริ่มทำ

digitaltransformation ในโรงงานหรือในสายการผลิต

-องค์กรที่กำลังหา solutionที่เข้ามาช่วยเพิ่ม OEE ได้จริง

-แผนกซ่อมบำรุง แผนกการผลิต ผู้จัดการโรงงาน ที่หา digital solution ในการซ่อมบำรุงเครื่องจักร

-องค์กรที่เริ่มทำ digital transformation ไปแล้วบ้าง แต่อยากได้องค์ความรู้เพิ่มเติม

ทางบริษัทจะนำองค์ความรู้เทคโนโลยีใหม่ๆมาพัฒนาต่อยอด ให้ระบบตอบโจทย์การทำงานเพื่อเพิ่มประสิทธิภาพมากยิ่งขึ้น

📍 สนใจระบบ #BiggoldERP และ #BiggoldIOT ติดต่อได้ที่

Website :

🌐https://www.biggolddigital.com

🌐Email: admin@biggolddigital.com

💻https://www.facebook.com/BiggoldERP

📱Tel : 099-6236446

📱Tel : 088-6324496

#BIGGOLDERP

#ERP

#ERPSYSTEM

#ERPMODULE

#ERPTECHNOLOGY

#ERPSOLUTION

#ERPSERVICE

#ERPSOFTWARE

#วางระบบERP

#พัฒนาระบบERP

#โปรแกรมERP

#APPLICATION

#SOFTWARE

#PROGRAM

#MOBILEAPP

#WEBAPP

#MMS

#TMS

#LOGISTIC

#IOT

#SMARTFACTORY

#AI

#SMARTIOT

#BIGGOLDIOT

#BIGGOLDFACTORY

#AFTERSALE

#MACHINELEARNING

#DEEPLEARNING

[melssblog]

Using data from Equipment Sensors, IoT has revolutionised manufacturing operations with a range of benefits such as: • Better identification of trends and areas for improvement • OEE for productivity monitoring - Machine/Shift/Variant/Operator wise • Data logging with time stamp for reverse traceability and real-time trend analysis • Implementation of foolproof Poka Yoke and 4M • Elimination of data entry by humans and digitalisation of the data register • Remote Monitoring of equipment • Streamlined manufacturing process using IoT-enabled devices • Predictive Maintenance to reduce unplanned downtime and increase productivity • Better tracking of assets and locations including humidity, air quality and temperature We provide a wide range of IoT Solutions for industry. For More Info: https://zurl.co/sQP1

[niyoindia]

Automation Centre of Excellence | Niyo India

Modular production systems and factory automation are key areas of Mechatronics that are increasingly becoming essential to the Digital Factory experience. In today’s world of Hybrid Factory and Cyber Physical Factory, these trends represent production automation integrated with continuous process automation. When it comes to showcasing your software solutions capabilities in the Internet of things or Industry 4.0, what you need is a state-of-the-art Automation Centre of Excellence, Industry 4.0 Center of Excellence or Center of Excellence for IOT.

NiYo Engineers supplies customised real production plants, discrete production factory, modular production system, flexible production system, biopharma plant or continuous process plants that emulate real-life industrial scenarios. You can integrate your Industry 4.0, IoT and IIoT solutions with our systems to demonstrate your software solutions capabilities to your customers with real-life simulations. Along with our products, we also supply the necessary data for you to develop Digital Twin using your solutions to enhance the Digital Factory experience.

NiYo Engineers can help you setup Industry 4.0 Center of Excellence to demonstrate specific use cases of your choice, such as predictive maintenance optimization, quality optimization, yield optimization, overall equipment effectiveness (OEE), machine utilisation, patterns of machine status, start time, stop time, total time, downtime analysis, production tracking, monitoring cycle time and much more. [Read More]

[dakshiiot]

Industry 4.0 and 6 Sigma: Enhancing Quality and Process Efficiency with DakshIIoT

In the fast-paced world of manufacturing, staying ahead requires a strategic blend of cutting-edge technologies and proven methodologies. Industry 4.0, often referred to as the fourth industrial revolution, and Six Sigma, a data-driven approach to process improvement, have emerged as formidable tools for enhancing quality and process efficiency. In this blog, we will explore how DakshIIoT, a leading provider of Industry 4.0 services, integrates these methodologies to bring about a paradigm shift in manufacturing excellence.

Industry 4.0 Unveiled

Industry 4.0 represents the integration of digital technologies into the manufacturing landscape, creating smart, interconnected systems. This revolution is marked by the implementation of the Internet of Things (IoT), Artificial Intelligence (AI), Big Data, and other advanced technologies. DakshIIoT, as a frontrunner in Industry 4.0 services, recognizes the transformative power of these technologies and their ability to revolutionize manufacturing processes.

Six Sigma: A Pillar of Quality Improvement:

On the other hand, Six Sigma is a disciplined, data-driven methodology aimed at reducing process variations and defects. It follows a structured approach of DMAIC (Define, Measure, Analyze, Improve, Control) to systematically improve processes. DakshIIoT leverages the power of Six Sigma to drive continuous improvement and ensure that the processes are optimized for maximum efficiency and quality.

The Marriage of Industry 4.0 and Six Sigma:

OEE Calculation

To enhance quality and process efficiency, DakshIIoT incorporates precise OEE calculations. OEE is calculated by multiplying Availability, Performance, and Quality. This provides a holistic view of the efficiency of manufacturing processes. By accurately measuring OEE, DakshIIoT helps identify areas for improvement and sets the foundation for data-driven decision-making.

OEE Optimization

Optimization is at the core of DakshIIoT’s approach. Through Industry 4.0 technologies, such as IoT sensors and real-time data analytics, processes are continuously monitored. This real-time monitoring enables rapid identification of bottlenecks and inefficiencies, allowing for immediate optimization. The integration of Six Sigma principles ensures that these optimizations are sustained over the long term.

Improving OEE

DakshIIoT understands that continuous improvement is the essence of both Industry 4.0 and Six Sigma. By adopting a culture of continuous improvement, processes are refined iteratively. This iterative refinement leads to a consistent increase in OEE, resulting in enhanced overall operational efficiency.

OEE Analysis

Comprehensive OEE analysis is a key component of DakshIIoT’s strategy. Through advanced analytics and AI, the company performs in-depth analysis of OEE data. This analysis uncovers patterns, trends, and root causes of inefficiencies. Armed with this knowledge, manufacturers can make informed decisions to further enhance their processes.

OEE Software

DakshIIoT offers state-of-the-art OEE software tailored to the specific needs of its clients. This software seamlessly integrates with existing systems, providing a user-friendly interface for monitoring and analyzing OEE metrics. The intuitive nature of the software ensures that manufacturers can easily navigate and derive actionable insights to drive improvements.

OEE Tracking System

A robust OEE tracking system is integral to DakshIIoT’s approach. Real-time tracking allows for immediate visibility into the performance of manufacturing assets. With this OEE tracking system, manufacturers can respond promptly to deviations from optimal performance, ensuring that quality and efficiency are maintained at all times.

In conclusion, the amalgamation of Industry 4.0 and Six Sigma, coupled with DakshIIoT’s expertise, provides a comprehensive solution for manufacturers aiming to enhance quality and process efficiency. By focusing on OEE calculation, optimization, improvement, analysis, software, and tracking systems, DakshIIoT empowers manufacturers to embark on a journey of continuous improvement in the Industry 4.0 era. Embrace the future of manufacturing with DakshIIoT – your partner for excellence in Industry 4.0 services.

[thrivemes]

Why the Time Period is Critical When Tracking OEE

It's important to remember that the goal of OEE (and machine downtime tracking) in general isn't just to highlight everything that is going right with your manufacturing efforts. Sure, everyone likes a nice pat on the back every now and again - a confirmation that their hard work is paying off. But you're also looking for opportunities to improve, too, which means paying attention to trends as they develop.

The issue is that OEE isn't a sprint - it's a marathon. The real actionable insight - the intelligence that will show you exactly what you need to do to thrive - will reveal itself over time. Instant gratification isn't what you're going for, here - if all your opportunities for improvement were obvious enough that they could be addressed overnight, the chances are high you would have recognized them and already done so by this point.

Time is of the Essence

All this is to say that if you're tracking machine downtime or OEE within the context of a single day, or even a week, you're not tapping into the full potential of the data being created. If all you're looking at is a single shift, you're not really learning anything valuable.

When the time period of your tracking efforts is too short, individual events become far too important to your OEE score. One period of unplanned downtime will have a major impact when, if it's the only such period you have in six months, it shouldn't necessarily be the case.

What you really need to be doing is looking at your tracking scores within the context of at least a month. That way, you'll be able to see things like performance and availability ebb and flow. Trends will start to reveal themselves.

Then, keep tracking. Compare those findings to what you're able to collect over the course of the next six months. What has changed? What initially appeared like a major issue that turned out to not be the case? What did you learn that you would have otherwise totally missed had your tracking period been 24 hours?

There's an old saying that reminds us the arc of progress is slow, but it is steady. Because the name of the game in terms of OEE tracking is continuous improvement, you need to look at what your solution is showing you the same way. You've already invested in the solution itself - you need to give ample time for that investment to pay off. Once you do, you'll identify gain after gain, and you'll have OEE tracking - not to mention patience - to thank for it. Anything else would be failing to tap into its full potential.

If you'd like to find out even more information about why you should carefully select your time period when tracking OEE across your manufacturing enterprise, or if you'd just like to discuss what equipment downtime tracking might be able to do for your business in a bit more detail, please feel free to contact the team at Thrive today.

Source URL:- https://labelsuperrecords.com/why-the-time-period-is-critical-when-tracking-oee/

[learningfrommiley]

Data Integration in Manufacturing: Enhancing Efficiency and Quality

Introduction

In the modern manufacturing landscape, data integration has emerged as a transformative force. The ability to seamlessly collect, aggregate, and analyze data from various sources within a manufacturing facility is revolutionizing the industry. Data integration in manufacturing not only drives efficiency and cost reduction but also significantly enhances product quality and innovation. This essay delves into the importance, benefits, challenges, and future prospects of data integration in the manufacturing sector.

The Importance of Data Integration in Manufacturing

Data integration in manufacturing refers to the process of unifying data from disparate sources, such as production machines, sensors, supply chain systems, and quality control devices, into a single, coherent system. This integrated data can then be analyzed to make informed decisions, optimize processes, and improve overall manufacturing performance. The importance of data integration in manufacturing can be summarized as follows:

Real-Time Visibility: Data integration provides real-time visibility into the entire manufacturing process. This allows manufacturers to monitor production, identify bottlenecks, and respond to issues promptly, ensuring uninterrupted operations.

Quality Assurance: By collecting and analyzing data at every stage of production, manufacturers can implement quality control measures proactively. This reduces defects, rework, and recalls, leading to higher product quality.

Cost Reduction: Data integration helps identify inefficiencies, optimize resource utilization, and reduce waste. Manufacturers can trim production costs, minimize energy consumption, and enhance resource allocation.

Predictive Maintenance: Manufacturers can use integrated data to predict equipment failures and perform timely maintenance, preventing costly downtime and improving overall equipment effectiveness (OEE).

Supply Chain Optimization: Integrated data facilitates better supply chain management by providing insights into demand, inventory levels, and supplier performance. This ensures the timely availability of materials and minimizes stockouts.

Innovation and Product Development: Integrated data can also fuel innovation by enabling manufacturers to identify trends, customer preferences, and opportunities for product improvement.

Benefits of Data Integration in Manufacturing

Improved Decision-Making: Data integration empowers manufacturing executives and managers with accurate, real-time information. Informed decisions can be made swiftly, responding to changing market conditions and production challenges effectively.

Enhanced Product Quality: Integrated data allows manufacturers to track and control every aspect of the production process, reducing defects and ensuring consistent product quality.

Increased Efficiency: Optimized processes and resources, enabled by data integration, result in streamlined operations and reduced lead times.

Cost Reduction: By identifying inefficiencies and minimizing waste, manufacturers can significantly reduce production costs.

Predictive Maintenance: Data integration enables predictive maintenance, reducing unplanned downtime and saving on maintenance costs.

Regulatory Compliance: In regulated industries, integrated data helps manufacturers maintain compliance with industry-specific standards and regulations.

Challenges in Implementing Data Integration

While data integration offers numerous benefits, it comes with its share of challenges:

Data Security: Protecting sensitive manufacturing data from cyber threats and ensuring data privacy is a paramount concern.

Data Silos: Many organizations have data stored in separate systems, making it challenging to integrate them seamlessly.

Legacy Systems: Older equipment and systems may not be designed for data integration, requiring costly upgrades or replacements.

Interoperability: Ensuring that different data sources and systems can communicate and share data effectively can be technically complex.

Talent Gap: Skilled data analysts and data engineers are needed to design, implement, and maintain data integration solutions.

Future Prospects

The future of data integration in manufacturing holds tremendous potential. Emerging technologies like the Internet of Things (IoT), artificial intelligence (AI), and machine learning (ML) will play a pivotal role in expanding the capabilities of data integration. Predictive analytics will become more sophisticated, enabling manufacturers to anticipate market trends, production issues, and customer demands with greater accuracy.

Additionally, the integration of data from the entire supply chain, including suppliers and customers, will become more prevalent, creating a seamless flow of information from end to end. This end-to-end integration will enhance agility, reduce lead times, and improve overall supply chain resilience.

Conclusion

Data integration is transforming the manufacturing industry by providing real-time insights, enhancing product quality, reducing costs, and driving innovation. Despite the challenges, manufacturers that embrace data integration will remain competitive and agile in an increasingly complex and dynamic global marketplace. As technology continues to evolve, data integration will only become more integral to the success of manufacturing operations, shaping the future of the industry.

[research--blog]

IoT in Manufacturing Market Worth $233.6 Billion by 2029

According to a new market research report titled, ’IoT in Manufacturing Market by Component (Platform, Connectivity), Application (Resource Optimization, Machine Inspection & Maintenance), End User (Automotive, Medical Devices) and Geography—Global Forecast to 2029’, the global IoT in manufacturing market is expected to register a CAGR of 13.7% from 2022–2029 to reach $233.6 billion by 2029. Download Free Report Sample Now @ https://www.meticulousresearch.com/download-sample-report/cp_id=5371

The rising demand for industrial automation in manufacturing and growing investments in Industry 4.0 are the major factors driving the growth of this market. However, data security and privacy issues in IoT can restrain market growth to a certain extent. Emerging 5G technology to help IoT adoption is expected to offer significant opportunities for the growth of this market.

Impact of COVID-19 on the IoT in Manufacturing Market

In the first quarter of 2020, the world was severely impacted by the COVID-19 pandemic. The effects of the COVID-19 outbreak can be seen throughout every industry, especially in the manufacturing sector. Business operations across the manufacturing sector have been disrupted due to shortages in raw materials & workforce, supply chain disruption, and restrictions on operating capacities. Despite the disruptive impact of COVID-19, organizations are planning to increase their investments in the Internet of Things (IoT) as a rapid increase in the adoption of industrial internet of things (IoT). Thus, the pandemic influenced the manufacturing industry to reduce its dependency on manual labor and adapt to advanced technologies such as AI, machine learning, and IoT.

With the adoption of IoT in manufacturing, manufacturers have observed improved productivity, higher quality, near-zero design error, energy efficiency, leaner process, flexibility in production scale, increased agility, improved predictability, and enhanced monitoring of the processes. Thus, the adoption of IoT technology influenced business operations worldwide to sustain business operations. Thus, the COVID-19 pandemic has positively impacted the global IoT in manufacturing market. This adoption trend of IoT technology is anticipated to continue and grow during the forecasted period.

Speak to our Analysts to Understand the Impact of COVID-19 on Your Business: https://www.meticulousresearch.com/speak-to-analyst/cp_id=5371

The global IoT in Manufacturing market is segmented by component (hardware, platform (network management, device management, application management, data management), services, and connectivity (satellite network, cellular network, near field communication (NFC), and other connectivity modes), deployment mode (on-premise and cloud-based), organization size (SMEs and large enterprises), application (surveillance & safety, quality management, resource optimization, inventory & warehouse management, machine inspection & maintenance, production planning, energy management, and smart robotics), end user (automotive, electronics & semiconductors, heavy metals & machine manufacturing, energy & utility, aerospace and defense, medical devices, pharmaceuticals, and other end users) and geography. The study also evaluates industry competitors and analyses the market at the country level.

Based on component, the global IoT in manufacturing market is segmented into hardware, platform, services, and connectivity. In 2022, the hardware segment is expected to account for the largest share of the global IoT in manufacturing market. The large market share of this segment is attributed to factors such as consistent engagement of the manufacturing sector in improving efficiency, reducing costs, and increasing overall equipment effectiveness (OEE). However, the platform segment is expected to register the highest CAGR during the forecast period. The rising adoption of IoT platforms in the manufacturing sector by various end users to improve operational efficiency drives the segment’s growth.

Based on deployment mode, the global IoT in manufacturing market is segmented into on-premise deployment and cloud-based deployment. In 2022, the on-premise deployment segment is expected to account for the larger share of the global IoT in manufacturing market. The large market share of this segment is attributed to a high preference for on-premise deployments among large enterprises and the availability of trained IT professionals & infrastructure. However, the cloud-based deployment segment is expected to register the highest CAGR during the forecast period. The growth of this segment is attributed to the increasing adoption of cloud computing in the manufacturing sector.

Quick Buy – IoT in Manufacturing Market- Global Opportunity Analysis And Industry Forecast (2022-2029), Research Report: https://www.meticulousresearch.com/Checkout/56276327

Based on organization size, the global IoT in manufacturing market is segmented into small and medium-sized enterprises (SMEs) and large enterprises. In 2022, the large enterprises segment is expected to account for the larger share of the global IoT in manufacturing market and is expected to register the highest CAGR during the forecast period. The growth of this segment is attributed to factors such as the strong IT infrastructure of large enterprises and the growing investment in the adoption of advanced technologies such as AI, IoT and blockchain by manufacturers.

Based on application, the global IoT in manufacturing market is segmented into surveillance & safety, quality management, resource optimization, inventory & warehouse management, machine inspection & maintenance, production planning, energy management, and smart robotics. In 2022, the surveillance & safety segment is expected to account for the largest share of the global IoT in manufacturing market. The large market share of this segment is attributed to factors such as the increasing need for monitoring production lines to promote a safer work environment for safe operation during the manufacturing process. However, the inventory & warehouse management segment is expected to register the highest CAGR during the forecast period. The rising adoption of IoT platforms for precise visibility into raw materials and components flow, work-in-process, and finished goods by providing real-time updates is driving the segment’s growth.

Based on end user, the global IoT in manufacturing market is segmented into automotive, semiconductors & electronics, heavy metals & machine manufacturing, energy & power, aerospace and defense, medical devices, pharmaceuticals, and other end users. In 2022, the automotive segment is expected to account for the largest share of the global IoT in manufacturing market. The automotive industry is extensively adopting automation, IoT, and robotics systems to enhance product quality, reduce work-in-progress time, and improve equipment reliability, promoting the market’s growth. However, the medical devices segment is expected to register the highest CAGR during the forecast period. The rapid growth of this segment is attributed to the growing adoption of digital technologies in medical device manufacturing operations.

Based on geography, the global IoT in manufacturing market is broadly segmented into North America, Europe, Asia-Pacific, Latin America, and Middle East & Africa. In 2022, Asia-Pacific is expected to account for the largest share of the global IoT in manufacturing market. Factors such as favorable government initiatives, technological innovation, the growing number of industrial organizations, and the increasing adoption of IoT devices to optimize operational efficiency drive the market’s growth. The region is also a hotbed of industrial robotics innovation, with China, Japan, and South Korea the three largest global markets. In addition, half of all APAC manufacturers are expected to have smart factories within three years.

The report also includes an extensive assessment of the key strategic developments adopted by the leading market participants in the industry over the past four years (2020–2022).

The key players operating in the global IoT in Manufacturing market are General Electric Company (U.S.), Emerson Electric Co. (U.S.), Intel Corporation (U.S.), Cisco Systems, Inc. (U.S.), SAP SE (Germany), International Business Machines Corporation (U.S.), Siemens AG (Germany), PTC Inc. (U.S.), Robert Bosch GmbH (Germany), Atos SE (France), Microsoft Corporation (U.S.), HCL Technologies Limited (India), Zebra Technologies Corporation (U.S.), Schneider Electric (France), Oracle Corporation (U.S.), Hitachi, Ltd. (Japan), and Software AG (Germany).

To gain more insights into the market with a detailed table of content and figures, click here: https://www.meticulousresearch.com/product/iot-in-manufacturing-market-5371

Scope of the Report:

IoT in Manufacturing Market, by Component 

Hardware                            

Platform

Network Management

Device Management

Application Management

Data Management

Services

Connectivity        

Satellite Network

Cellular Network

Near Field Communication (NFC)

Other Connectivity Modes

IoT in Manufacturing Market, by Deployment Mode     

On-premise Deployment Mode

Cloud-based Deployment Mode                      

IoT in Manufacturing Market, by Organization Size     

Small and Medium-sized Enterprises (SMEs)

Large Enterprises

IoT in Manufacturing Market, by Application 

Surveillance & Safety

Quality Management

Resource Optimization

Inventory & Warehouse Management

Machine Inspection & Maintenance

Production Planning

Energy Management

Smart Robotics                  

IoT in Manufacturing Market, by End User                    

Automotive

Electronics & Semiconductors

Heavy Metals & Machine Manufacturing

Energy & Utility

Aerospace and Defense

Medical Devices

Pharmaceuticals

Other End Users

IoT in Manufacturing Market, by Geography                

North America     

U.S.

Canada

Europe   

U.K.

Germany

France

Italy

Spain

Rest of Europe

Asia-Pacific         

Japan

China

India

South Korea

Rest of Asia-Pacific

Latin America      

Middle East & Africa

Download Free Report Sample Now @ https://www.meticulousresearch.com/download-sample-report/cp_id=5371 Related Report:

Smart Manufacturing Market - Global Opportunity Analysis and Industry Forecast (2022–2029) https://www.meticulousresearch.com/product/smart-manufacturing-market-5265

[smartfactorymom]

Why Food and Beverage Manufacturers Need to Integrate with Smart Systems?

The food and beverage manufacturing industry is going through a transformation, due to the integration of technology and automation. This shift not changes how things are done but also brings improvements in efficiency, quality and safety. It benefits both producers and consumers alike. Let’s explore some of the advancements in technology and automation such as twins, meticulous tracking systems, robotics and automation as well as artificial intelligence and machine learning integration.

The world of food and beverage manufacturing is experiencing a change as it embraces the age. Recent times have witnessed a shift towards technology and automation leading to the emergence of factories and sparking discussions about digital transformation. The potential lies in achieving efficiency levels, improved quality control measures and enhanced safety standards within the industry – all of which will have outcomes for consumers, manufacturers and the communities they serve.

By exploring concepts like transformation and examining the landscape of manufacturing, the goal is to provide valuable insights into how Smart Factories are poised to revolutionize the food and beverage industry.

Digital Transformation in the Food and Beverage Manufacturing Industry

One of the drivers behind the digital transformation in the food and beverage manufacturing industry is the pressing need for increased efficiency and productivity.

To improve efficiency, reduce costs and enhance Overall Equipment Effectiveness (OEE) as well as production outputs, food and beverage manufacturers are constantly seeking ways to optimize their processes. The integration of technologies such as Artificial Intelligence (AI) machine learning and robotics offers a solution to achieve these goals. For example, by leveraging AI and machine learning algorithms, manufacturers can quickly analyze volumes of data with accuracy, enabling real time quality decision making. Additionally, robotics plays a role by handling repetitive tasks that would otherwise require human effort. This allows human workers to focus their energy on innovative assignments.

Moreover, there is an increasing attention on sustainability which puts pressure on enterprises to reevaluate their practices and explore environmentally friendly approaches.

In this context, technology emerges as a force. By combining creativity with capabilities, businesses have an opportunity to embrace sustainability.

To give an example, AI and machine learning can be used to optimize supply chains reducing waste and increasing efficiency. The shift towards factories is not about technology; it also has cultural and environmental implications.

Smart Manufacturing Trends in Food and Beverage Industry

The food and beverage industry is currently experiencing changes in manufacturing. These include

Tracking the journey of products from farm to table ensuring transparency.

Tracing products from their source in the field to their delivery point.

Implementing factories that use robots for efficient processes.

Using laser guided vehicles along with IoT for connectivity.

While these trends offer potential, it is important for food and beverage manufacturers to approach them cautiously.

To fully leverage the advantages of manufacturing, companies need to integrate this technology into their core business systems.

Here are three important factors to consider when embracing manufacturing in the food and beverage industry:

Mobile Barcoding for Smooth Connectivity: Embrace the use of mobile barcoding to ensure inventory updates are in time. This enables traceability paths that instantly update an ERP system. By integrating this technology, companies can quickly adjust production based on demand and shortages maintaining up to date records and enhancing flexibility.

Prioritize Traceability: Traceability is a benefit of manufacturing especially for food producers. It allows organizations to respond promptly and accurately during product recalls or safety concerns. With mobile inventory tracking, all products can be meticulously recorded, making it easier to identify contaminated inventory. Without integration, recalls may involve batches, negatively impacting productivity and profitability. Traceability also improves field mobility by providing offline solutions that keep workers connected in remote areas ensuring no transactions are lost.

Embrace Operational Agility: The current business landscape requires adaptability for success. A strong supply chain strategy combined with inventory solutions and food and beverage software provides real time insights, throughout the warehouse and delivery process.

Manufacturers have the ability to quickly adapt their production processes in response to changes in demand, unexpected shortages and unforeseen interruptions. For example, a company specializing in consumer goods packaging successfully managed an increase in production during the pandemic by utilizing supply chain software and food and beverage software. This allowed them to promptly reassign tasks and meet the rising demand.

Why is the Smart Factory Manufacturing Operations Management (MOM) system considered a smart solution for the food and beverage manufacturing industry?

Think of the Smart Factory MOM system as an intelligent assistant specifically designed for food and beverage manufacturing. It's like having a trusted companion that ensures everything runs seamlessly.

This system oversees every stage of food production until it reaches its to-be consumed state. It diligently monitors each step ensuring that everything proceeds smoothly.

In case any issue arises, such as machinery breakdown, the MOM system quickly alerts someone so that they can address it before it escalates into a problem. It's akin to having a superhero who detects trouble and calls for assistance!

However, the capabilities of the MOM system extend beyond problem solving; it also excels at predicting issues. It can identify when machines may require maintenance even before they malfunction or break down.

You know what's really cool? The Smart Factory MOM has this ability to anticipate when there will be a demand, for food and prepare accordingly. But here's the thing it's not about machines. Smart Factory also values the input of its workers.

They can freely share their ideas and this fantastic MOM system helps foster collaboration among everyone. In the world of food and drink where precision is the key, the Smart Factory MOM acts like a sidekick. It keeps an eye over operations, resolves any issues that arise, and even seems to predict what will happen next. It's like having a friend who ensures that everything tastes delicious and runs smoothly according to the schedule.

[rawcubes]

Proactive Maintenance with Advanced Machine Monitoring Software

Proactive Machine Maintenance for Industry 4.0 with Machine Monitoring So iDataOps

Rawcubes' cutting-edge industrial machine monitoring platform automatically monitors and manages all connected devices. Utilizing advanced analytics and machine learning algorithms, iDataOps a machine monitoring system analyzes data generated by production-level equipment, such as temperature, vibration, and power consumption. By monitoring equipment behavior and performance metrics, the machine monitoring system can detect patterns that may indicate potential failures or issues.

The platform is built on top of DataBlaze, Rawcubes' industrial data management software, and is specifically designed to "listen" to all onboarded production equipment. It continuously monitors equipment behavior, utilization, power consumption, and data generated at the equipment level.

The need for a machine monitoring system stems from its ability to significantly reduce production downtime and ensure a smooth production flow. Unscheduled maintenance or repairs can lead to substantial financial losses for companies. iDataOps plays a crucial role in preventing unexpected downtime by predicting equipment failures and maintenance needs in advance. This allows maintenance teams to plan and schedule activities proactively, leading to increased productivity and reduced costs.

Several examples illustrate the machine monitoring system's effectiveness. iDataOps can identify wear and tear on industrial equipment, allowing proactive replacement before breakdowns occur. It can also monitor lubrication levels to prevent equipment failure due to insufficient lubrication. Additionally, the platform can detect excessive vibrations that may lead to premature equipment failure.

The key components of the iDataOps platform include the Organization Workbench, Customer Workbench, and Machine Onboarding Workbench. These sections facilitate the onboarding of organizations and customers and provide a comprehensive overview of production-level data, enabling the tracking of different versions of products and identifying emerging patterns or trends.

The iDataOps platform's real-time insights at the machine level are a major advantage. By "listening" to equipment in real-time, the machine monitoring system displays OEE metrics, allowing users to monitor each machine individually and gain valuable insights into their performance. The platform also allows users to raise tickets and assign priority levels for immediate issue resolution, supported by service management history for diagnostics.

To ensure comprehensive coverage, the platform fetches data directly from connected devices and utilizes proprietary data models and ML-based predictive maintenance models to provide real-time insights for end-to-end operations at the machine level.

Users do not require extensive technical skills to use this machine monitoring system effectively. The platform is designed to be user-friendly and intuitive, requiring only basic skills. This accessibility empowers operations personnel to easily onboard devices and utilize the machine monitoring system’s capability for real-time insights for improved decision-making.

For a deeper understanding of iDataOps our machine monitoring software, additional blogs on Rawcubes' website offer valuable insights into how the platform empowers companies to optimize their machine monitoring and maintenance strategies. With Rawcubes' intelligent data management and machine monitoring solution, businesses can digitize their manufacturing processes and prepare for the challenges and opportunities of Industry 4.0. Schedule a demo with us today and unlock the full potential of iDataOps!

[trend-report]

„Smart Manufacturing – der intelligente Weg “

TREND REPORT sprach mit Malte Dieckelmann, Vice President Enterprise Software Sales - EMEA, Rockwell Automation, weltweit führender Anbieter von industriellen Automatisierungs- und Informationslösungen, über die Vorteile von mehr Intelligenz in der industriellen Fertigung und was die Daten-Cloud damit zu tun hat. Herr Dieckelmann, auf was müssen sich Unternehmen beim Thema Smart Manufacturing einstellen? Smart Manufacturing gewinnt bei Unternehmen zunehmend an Bedeutung. Wer profitabler wachsen, seine Qualität steigern, oder nachhaltiger produzieren will, der kommt an datenbasierter Intelligenz in der Fertigung nicht vorbei. Entscheidend für die vernetzte Produktion ist dabei ein performantes Produktionsleitsystem, also ein Manufacturing Execution System (MES). Was sind Ihrer Erfahrung nach die Triebfedern für Entscheidungsträger bei der Einführung intelligenter Fertigungslösungen? Wir führen bei Rockwell Automation hierzu regelmäßig Gespräche mit unseren Kunden. Rund die Hälfte strebt primär eine Verbesserung ihrer Marktposition an. Die Entscheider suchen Wege, flexibler und schneller auf sich ändernde Marktbedingungen reagieren zu können. Aber auch der nachhaltige Umgang mit Ressourcen und eine nachhaltigere, umweltschonendere Produktion sind für viele Unternehmen von großer Relevanz. Mit Smart Manufacturing, der Nutzung des IoT und intelligenten MES-Ansätzen führen wir bei Rockwell die operative Technologie und die Informationstechnologie zusammen, um diesen Herausforderungen zu begegnen und die Effizienz zu steigern. Worin sehen Sie die zentralen Vorteile einer intelligenteren Fertigung? Erfolgreich sind unsere Kunden vor allem aufgrund ihrer Kompetenz im Bereich der operativen Technologie. Nicht wenige aber arbeiten noch sehr analog, teilweise sogar noch mit Stift und Papier. Die Vorteile einer MES-Einführung liegen hier natürlich anders, als bei Kunden, die in ihrer digitalen Transformation schon weiter fortgeschritten sind. Ausnahmslos jedes Unternehmen aber gewinnt durch Smart Manufacturing an Flexibilität, was letztlich geringere Kosten, höhere Erträge und zusätzliche Geschäftsmöglichkeiten bedeutet. Ob Mittelständler oder Konzern, bei der Einführung von MES beginnen wir häufig mit einer einzigen Anlage bzw. Fertigungslinie. Im Laufe der Zeit wirken sich die Vorteile der MES-Implementierungen auf das ganze Werk oder sogar mehrere Werke aus. Hier ist es wichtig zu überlegen: Was sind die Veränderungen, die Lehren, und die Technologien, die wir in Zukunft in Betracht ziehen müssen, und wie können die Mitarbeiter erfolgreich in diese Transformation eingebunden werden? Weitere Vorteile ergeben sich dann etwa bei der technischen Befähigung durch Augmented Reality, in Anwendungsfällen des Internet of Things (IoT), oder bei Messungen der Betriebseffizienz (OEE und Production Monitoring). Wie genau kann ein MES zu mehr Kosteneffizienz und zusätzlichen Einnahmequellen führen? Mit der Einführung profitieren Unternehmen vor allem durch eine Verringerung des Ausschusses. Zudem bekommen sie bessere Einsicht in die Gesamtanlageneffektivität, möglicherweise sogar in Echtzeit. Durch ein neues Level an Flexibilität in der eigenen Produktion werden automatisch Ressourcen freigeschaufelt, die dann andernorts vorteilhaft eingesetzt werden können. Worin sehen Sie die zentralen Herausforderungen bei einer MES-Einführung und wie beeinflussen diese den gesamten Prozess? In der Implementierungsphase sind mehrere Ebenen zu beachten. Zentrale Themen vieler Kunden sind dabei Cybersecurity und Datensicherheit. Bei Rockwell Automation setzen wir daher sowohl auf unsere eigene Cybersecurity- Produkt- und Projektkompetenz als auch auf enge Partnerschaften mit Spezialisten wie Claroty, Fortinet oder Cisco. Viele unserer Kunden profitieren zudem bereits von der Cloud. Wir haben eine großartige Partnerschaft mit Microsoft, die es ermöglicht, die Stärken verschiedener Partner zu kombinieren. Mit „Plex“ bieten wir ein Rockwell-eigenes, cloudbasiertes MES-Produkt an, das einen offenen und ganzheitlichen Ansatz verfolgt. Wie genau setzen Sie die Cloud und „Plex“ ein, um Ihre Kunden zu unterstützen? Der Vorteil der Cloud ist, dass ein Großteil unserer Kunden sie bereits nutzt. Alle wichtigen Daten sind an einem zentralen Ort gespeichert und können hier abgerufen werden. „Plex“ ist dabei mehr als nur ein cloudbasiertes MES-System. Es ist erfolgreich, weil es über das „klassische“ MES hinaus, auch Enterprise Ressource Planning, Lieferkettenmanagement, die Überwachung der Anlagenleistung, das Qualitätsmanagement und viele weitere Aspekte für Kunden individuell zusammenführt. Unternehmen erhalten durch Lösungen wie „Plex“ mehr Informationen und damit tiefere Einblicke in die ­Performance ihrer Anlagen. Das ist besonders wichtig mit Blick auf die Skalierung, wenn sie mehrere Fertigungsanlagen in verschiedenen Ländern be­­treiben. Das Ergebnis ist simpel: Als multinationaler Konzern helfen wir Unternehmen dabei, durch eine intelligentere, zeitgemäße Fertigung Wachs­tum zu generieren und zudem die Vorteile einer bestehenden Cloud-Infrastruktur noch besser zu nutzen. Und das Ganze idealerweise schnell, flexibel und mit viel Industriekompetenz. www.rockwellautomation.com   Dieser Beitrag ist freigegeben unter einer CC-BY-ND 3.0 DE Lizenz https://creativecommons.org/licenses/by-nd/3.0/de/ Die Bildrechte unterliegen einem gesonderten Urheberrecht.   Read the full article

[essglobe]

HOLISTIC ANALYSIS of ENTIRE FMCG DATA

• Streamline production & supply chain efficiencies, reduces cost, and resource allocation. • Take the products to the right time, Redirect R&D investment, and improve returns of marketing effects. • Gain customer insights, Customize promotional price, and Enhance customer retention percentage.

INDUSTRY 4.0 AND ESS

ESS BI Solutions helps you advance your analytic complexity level and create new workflow in the organization. It helps the business to collect data from ERP and derive holistic viewpoint. BI in FMCG operations generate and capture data from all their processes. This data can help the organization generate game-changing insights and enables data-driven strategic decision.

Perform Unified Analytic

Business Intelligence in FMCG Industry combines data from various sources, be it from IoT devices, legacy systems, packaging units, distribution unit, and manufacturing units, and create intuitive dashboards to get clear visibility of your entire operations. Drill-down to get to the granularity of any causative factors that may help you to enhance operational efficiency. With smart UI, easily adapt this data-driven decision-making across the entire organization.

Customer Insights

Business Intelligence in FMCG can handle massive data sets, may combine all the customer data gathered by many corporate departments and sources without information duplication and data silos. You may segment your consumer base and foresee market trends by examining the tastes and purchasing behavior of your customers. Additionally, it gives all of your employees that interact with your customers across departments the ability to tailor their experience simultaneously, improving engagement and raising the possibility of cross-selling or up-selling products to increase their lifetime value.

Monitor OEE (Overall Equipment Effectiveness)

Using advanced analytics determines and improves the manufacturing plant's productivity. To track OEE, BI in FMCG collect and analyze all the structured and unstructured data from the operators, machines, sensors, and IoT devices. Discover and improve the efficiency of each equipment, plant, and production setting as a whole. Measure a range of important KPIs, including delay and downtime. To maximize maintenance, link availability, performance, and quality to efficiency. The component frequently failing can be identified and proactively fixed by floor managers utilizing real-time tool and process monitoring to prevent production losses. Evaluate performance rate, target deviance, causes of and incidents related to downtime and more.

Forecast Demand

Using machine learning, predict demand using past purchases and other forward-looking data. Business Intelligence in FMCG industry conducts what-if analyses to learn about and comprehend numerous possibilities in order to prevent unsold inventory, reduce risk, enhance sales tactics, and expand growth potential. Develop specific possible results and prospective plans.

Supply Chain Management

Obtain a complete picture of your supply chain and go deeper to gain more knowledge. For the purpose of identifying current supply chain difficulties and warning signs, connect to internal and external data source such as ERP. BI in FMCG maintains a close eye on consumer demand and trends while managing cost, quality, orders, and inventories effectively. To acquire the greatest pricing, quality, and delivery, evaluate vendors and compare their performance. Manage the supply chain effectively by matching supply and demand with predictive analytics.

Marketing Mix Model for Campaign Analysis

In the fast-moving consumer goods (FMCG) industry, effective marketing campaigns are crucial to success. This is where the Marketing Mix Model for Campaign Analysis with Power BI comes in. It uses business intelligence (BI) tools to track and analyze various aspects of a campaign, including pricing, promotion, product, and placement. By utilizing this model, FMCG companies can gain valuable insights into which elements of their campaigns are most effective and make data-driven decisions to optimize future campaigns. BI in the FMCG industry has become increasingly important in recent years, as companies strive to stay competitive in a crowded market. With Power BI, companies can easily gather and analyze large amounts of data, allowing them to make informed decisions quickly and efficiently. By utilizing the Marketing Mix Model for Campaign Analysis with Power BI, FMCG companies can stay ahead of the game and continue to grow their business.

Leveraging the Analytics to increase customer retention & loyalty

The capacity to keep customers and earn their loyalty can determine whether a corporation succeeds or fails in an increasingly hypercompetitive market. By avoiding weak places, businesses are using data analytics to keep the valuable clients they already have. Businesses can examine customer behavior and experience to seize important chances to affect customer behavior, customer experience, and customer retention.

[inteliiotblog]

The Advantages and Trends in Asset Management with IoT - Inteliiot

Asset management is critical for manufacturing companies looking to gain a competitive edge. As a result, adopting IoT-based innovations for asset management has become increasingly popular. It helps improve overall equipment effectiveness (OEE) by monitoring availability, performance, and quality.

Poor asset management and production can cause delays in the supply chain and hinder successful business operations. However, IoT-powered asset tracking offers effective and efficient management, ultimately enhancing operational efficiency and facilitating the development of business models for tracking asset performance throughout its life cycle.

What advantages does IoT-based asset management offer?

IoT-based asset management allows companies to streamline operations and increase profits. Here are some benefits of using IoT-powered asset management:

Real-time visibility: IoT-based asset management offers real-time visibility into the location, health, and performance of assets, optimizing operations, reducing downtime, and increasing productivity. Read more....

Source Link:- https://www.inteliiot.com/blogs/the-advantages-and-trends-in-asset-management-with-iot/

[dakshiiot]

The Future of Industrial Robotics: Trends and Predictions

In the ever-evolving landscape of Industry 4.0, industrial robotics have become the cornerstone of manufacturing processes. As we look ahead, it’s crucial to understand the trends and predictions shaping the future of industrial robotics. At DakshIIoT, we specialize in providing cutting-edge Industry 4.0 services, focusing on OEE calculation, OEE optimization, improving OEE, OEE analysis, OEE software, and OEE tracking systems. In this blog post, we will delve into the transformative trends and predictions that are set to revolutionize the world of industrial robotics.

Advanced Automation and AI Integration:

One of the most significant trends in industrial robotics is the integration of advanced automation and artificial intelligence (AI). As robotics technology advances, robots are becoming smarter, and capable of learning and adapting to complex tasks. At DakshIIoT, we harness the power of AI to enhance OEE calculation and optimization, providing our clients with intelligent solutions to improve their manufacturing processes.

Collaborative Robotics (Cobots)

Collaborative robots, or cobots, are designed to work alongside human workers, enhancing efficiency and safety in manufacturing environments. These robots can handle intricate tasks, allowing human workers to focus on more strategic and creative aspects of production. At DakshIIoT, we offer OEE tracking systems integrated with cobots, ensuring seamless collaboration between man and machine, leading to improved OEE analysis.

Predictive maintenance, enabled by IoT sensors and data analytics, is revolutionizing industrial robotics. By monitoring the performance of robotic systems in real-time, manufacturers can identify potential issues before they escalate, minimizing downtime and maximizing productivity. Our OEE software incorporates predictive maintenance algorithms, ensuring optimal performance and reducing unplanned downtime significantly.

Human-Robot Collaboration in the Supply Chain

Industrial robots are no longer confined to the manufacturing floor; they are increasingly being integrated into the entire supply chain. From warehousing to logistics, robots are streamlining operations and enhancing efficiency. At DakshIIoT, we provide solutions that encompass the entire supply chain, optimizing OEE calculation and improving overall productivity.

Cloud Robotics and Remote Monitoring

Cloud robotics allows manufacturers to remotely monitor and control robotic systems from anywhere in the world. This trend not only enhances flexibility but also facilitates real-time data analysis and decision-making. Our OEE tracking systems are cloud

-enabled, providing our clients with instant access to critical data and insights, leading to continuous OEE optimization.

Sustainability and Green Robotics

The future of industrial robotics is not just about efficiency and productivity; it’s also about sustainability. Green robotics, characterized by energy efficiency and eco-friendly materials, is gaining prominence. At DakshIIoT, we prioritize sustainable practices in our solutions, ensuring that our client’s operations align with environmental conservation efforts while maintaining top-notch OEE analysis and software performance.

In conclusion, the future of industrial robotics is bright and dynamic, driven by innovative technologies and a focus on efficiency, collaboration, and sustainability. At DakshIIoT, we are at the forefront of this revolution, providing comprehensive Industry 4.0 services that encompass OEE calculation, OEE optimization, improving OEE, OEE analysis, OEE software, and OEE tracking systems. By embracing these trends and predictions, manufacturers can unlock new levels of productivity, efficiency, and success in the era of industrial robotics.