Vulcanizing the Tire Plant Operations

| April 29, 2019
VULCANIZING THE TIRE PLANT OPERATIONS
The Tire industry has always been at the forefront of technological innovations, often leading the way, for the rest of the pack. With the emergence of innovative technologies, ultra-modern production facilities and the rising global demand, the sector is poised to grow further. According to Global Industry Analysts, the global tire industry is slated to reach 2.5 billion units of production by 2022.

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ICCNexergy, Inc.

ICCN+Palladium is excited to announce that it is now Inventus Power. On December 11, 2015 we will deactivate this account. Please follow www.linkedin.com/company/inventus-power for all news and updates.

OTHER ARTICLES

AGV ROI Starts with a Delivery Commitment

Article | January 4, 2022

So much emphasis has been placed on features, advantages, and benefits; too little attention has been paid to delivery dates. The best automation solution on paper means nothing if it cannot be delivered in 2022. Selling the sexy sizzle of new, clever, even remarkable AGVs means nothing if manufacturers and distribution centers cannot take delivery of the product until 2023. Throughout industrial manufacturing and distribution the lead time from many AGV manufacturers is more than a year. That means product ordered in Q1 2022 will not be delivered until the following year. That is an absurd lead time and reflects poor planning and unnecessary supply chain constraints.

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Real-Time Data Collection in Manufacturing: Benefits and Techniques

Article | January 12, 2022

Real-time manufacturing analytics enables the manufacturing base to increase its efficiency and overall productivity in a variety of ways. Production data is an effective means of determining the factory's efficiency and identifying areas where it might be more productive. “Without big data analytics, companies are blind and deaf, wandering out onto the web like deer on a freeway.” – Geoffrey Moore, an American Management Consultant and Author Creating a product-specific data collection may assist you in determining and visualizing what needs to be improved and what is doing well. In this article, we'll look at why manufacturing data collection is vital for your organization and how it may help you improve your operations. Why is Manufacturing Data Collection so Critical? Visibility is the key benefit that every manufacturer gets from manufacturing data collection. By collecting real-time data, or what we refer to as "shop floor data," manufacturers better understand how to assess, comprehend, and improve their plant operations. Manufacturers can make informed decisions based on detailed shop floor data. This is why having precise, real-time production data is critical. “According to Allied Market Research, the worldwide manufacturing analytics market was worth $5,950 million in 2018 and is expected to reach $28,443.7 million by 2026, rising at a 16.5% compound annual growth rate between 2019 and 2026.” For modern manufacturers, the advantages of data collection in manufacturing are numerous. The manufacturing industry benefits from production data and data-driven strategy in the following ways. Substantial reduction in downtime by identifying and addressing the root causes of downtime. It increases manufacturing efficiency and productivity by minimizing production bottlenecks. A more robust maintenance routine that is based on real-time alerts and machine circumstances. Improvements in demand forecasting, supplier scoring, waste reduction, and warehouse optimization reduce supply chain costs. Higher-quality goods that are more in line with customers' wishes and demands depending on how they are utilized in the current world. So, after looking at some of the significant benefits of real-time manufacturing analytics, let’s see what type of data is collected from production data tracking. What Sorts of Data May Be Collected for Production Tracking? Downtime: Operators can record or track downtime for jams, cleaning, minor slowdowns, and stoppages, among other causes, with production tracking software. In the latter scenario, downtime accuracy is optimized by removing rounding, human error, and forgotten downtime occurrences. The software also lets you categorize different types of stops. Changeovers: Changeovers can also be manually recorded. However, changeovers tracked by monitoring software provide valuable data points for analysis, considerably reducing the time required for new configurations. Maintenance Failures: Similar to downtime classification, the program assists in tracking the types of maintenance breakdowns and service orders and their possible causes. This may result in cost savings and enable businesses to implement predictive or prescriptive maintenance strategies based on reliable real-time data. Items of Good Quality: This is a fundamental component of production management. Companies can't fulfill requests for delivery on schedule unless they know what's created first quality. Real-time data collection guarantees that these numbers are accurate and orders are filled efficiently. Scrap: For manufacturers, waste is a significant challenge. However, conventional techniques are prone to overlooking scrap parts or documenting them wrong. The production tracking system can record the number and type of errors, allowing for analysis and improvement. Additionally, it can capture rework, rework time, and associated activities. WIP Inventory: Accurate inventory management is critical in production, yet a significant quantity of material may become "invisible" once it is distributed to the floor. Collecting data on the movement and state of work in progress is critical for determining overall efficiency. Production Schedule: Accurate data collection is essential to managing manufacturing orders and assessing operational progress. Customers' requests may not be fulfilled within the specified lead time if out of stock. Shop floor data gathering provides accurate production histories and helps managers fulfill delivery deadlines. Which Real-time Data Collection Techniques Do Manufacturers Employ? Manufacturers frequently employ a wide range of data collection techniques due to the abundance of data sources. Manual data collection and automated data collection are two of the most common data collection methods. Here are a few examples from both methods: IoT: To provide the appropriate information to the right people at the right time with the correct shop floor insight, IoT (Internet of Things) sensor integration is employed. PLC: The integration of PLC (Programmable Logic Controller) is used to measure and regulate manufacturing operations. HMI: It can provide human context to data by integrating line HMI (Human Machine Interface) systems (such as individual shop terminals like touch screens located on factory floor equipment). SCADA: Overarching management of activities with SCADA (Supervisory Control and Data Acquisition) systems. CNC and Other Machines: Integrating CNC and other machines (both new and older types) to keep tabs on production efficiency and machine well-being is a must these days. Final Words One of the most challenging aspects of shop floor management is determining what to measure and what to overlook. The National Institute of Standards and Technology recently conducted a study on assisting manufacturing operations in determining which data to collect from the shop floor.Additionally, you may utilize the manufacturing data set described above to obtain information from your manufacturing facility and use it strategically to improve operations, productivity, efficiency, and total business revenue in the long term. FAQ What is manufacturing analytics? Manufacturing analytics uses operations and event data and technology in the manufacturing business to assure quality, improve performance and yield, lower costs, and optimize supply chains. How is data collected in manufacturing? Data collection from a manufacturing process can be done through manual methods, paperwork, or a production/process management software system.

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How Collaborative Robots Are Revolutionizing the Manufacturing Industry

Article | December 10, 2021

A new form of robot is entering manufacturing plants all around the globe. Instead of being locked away in their own work cell, collaborative robots work side by side with their human counterparts. Together, they form the manufacturing crew of the future. Collaborative robots, or cobots, are more flexible, easy to use, and safer than industrial robots. Instead of ending up abandoned in a corner, they are proving to be serious expansions of production capacity leading to better ways of creating superior quality products. 1.1 A New Breed of Bot Cobots are a new type of automation product with their own ISO standards for safety and usability. For a robot to qualify as a cobot, it has to be used for tasks of a collaborative nature while sharing all or part of its reach space with human operators. So it is not the product alone that classifies it as a cobot. Industrial robots must be expertly programmed for one specific job along the production line. This requires hard line coding and endless tweaking and testing, which together with other factors make for a sizable upfront investment. Not so with collaborative robots. Cobots may look similar to traditional robots in some ways, but they are much easier to install and program. This foregoes the need to cooperate with a robotic integration service. Their lightweight and friendly form factor lets manufacturers conveniently relocate them on the shopfloor from one project to another. This renders the robotics technology perfect for a data-driven, Industry 4.0 work environment. Cobots can side with traditional machinery and additive manufacturing equipment, aided by artificial intelligence and cloud connectivity while embedded in a networked environment rich with smart sensors and mixed reality interfaces. 1.2 A Unique Blend of Benefits Because it is fairly straightforward to reprogram a cobot to various tasks, they are perfect for high-mix, low-volume work to meet the rising demand for ultra-customized products. They can also do multiple tasks in unison, such as alternatingly loading a machine and finishing parts from the previous cycle. Here are some other advantages in addition to flexibility: • Low investment. Cobots typically cost a fraction of the price of an industrial robot, but they offer much lower payload and reach. ROI is typically one to two years. • Safety. With rounded surfaces, force-limited joints, and advanced vision systems, cobots are exceptionally safe. This reduces the risk of injury due to impact, crushing, and pinching. Driverless transport systems are wheeled mobile robots that immediately halt when their lasers detect the presence of a nearby human being. • Accuracy. Cobots score well on accuracy with 0.1mm precision or well below that. While they do typically sacrifice speed, dual-mode cobots can be converted to fully-fledged tools of mass production that run at full speed in their own safeguarded space. • Easy to program. Many brands offer user-friendly programming interfaces from beginner to expert level. This reduces the need for continuous availability of expensive and scarce expertise while giving current employees an incentive to upskill. And because they can be deployed within hours, cobots can be leased for temporary projects. • Research. Small processing plants, agile start-ups, and schools can invest in cobots to experiment with ways to automate processes before committing to full automation. 1.3 Cobot Activity Repertoire Cobots are perfect candidates for taking over strenuous, dirty, difficult, or dull jobs previously handled by human workers. This relieves their human co-workers from risk of repetitive strain injury, muscle fatigue, and back problems. They can also increase job satisfaction and ultimately a better retirement. The cobot’s program of responsibilities includes: • Production tasks such as lathing, wire EDM, and sheet stamping. • Welding, brazing, and soldering. • Precision mounting of components and fasteners, and applying adhesive in various stages of general assembly. • Part post-finishing such as hole drilling, deburring, edge trimming, deflashing, sanding, and polishing. • Loading and unloading traditional equipment such as CNC and injection molding machines, and operating it using a control panel to drastically reduce cycle times. • Post-inspection such as damage detection, electronic circuit board testing, and checking for circularity or planarity tolerances. • Box-packing, wrapping, and palletizing. • Automated guided vehicles (AGVs) and autonomous mobile robots (AMRs) assist with internal transport and inventory management. 1.4 No-Code Programming While an industrial robot requires the attention of a high-paid robotics engineer, anyone with basic programming savviness can install and maintain a collaborative unit. Brands are releasing more and more kits for quick installation and specific use cases. Instead of being all numbers and line-coding, current user interaction is exceptionally people-focused. At the lowest skill level, lead-through programming lets operators physically guide the cobot’s end-of-arm-tool (EOAT) through the desired motion path, after which it will flawlessly replicate the instructed behaviour. It is also possible to enter desired waypoints as coordinates. At the highest level, it is of course still possible to have full scripting control. An intermediate step is visual programming interfaces. These let users create blocks of functionality that they can string together into more advanced action sequences, while entering the appropriate parameters for each function such as gripping strength, screwing tightness, or pressing force. These UIs come in the form of in-browser or mobile apps. Based on a 3D-CAD model of the machine and its industrial environment, a digital twin of the cobot can simulate and optimize its operations, for example to prevent collisions. It also lets operators remotely monitor and adjust the machine while it’s running. All the while, back-end artificial intelligence can do its analyses to find further efficiency improvements. 3D models of the to-be-manufactured product can be imported for edge extraction of complex surfaces. These will then be converted into the cobot’s desired movement trajectories instead of tedious manual programming. This makes them feasible to implement for highly dexterous tasks like welding curved hydroformed metal parts or sanding and polishing the most intricate of 3D printed geometries. Interfacing directly with the robot is becoming increasingly human-centered as well. Future cobots will respond to voice interaction as well as touch input, eradicating the screens-and-buttons paradigm of current devices. Some brands are giving the cobot a face with emotional expressions, hoping to lower the barrier to adoption. The upcoming generation of cobots can even respond to body language, as well as show its intentions by projecting light to where they are about to reach or move next. 1.5 A Human World Ultimately, the objective of any company is to create value for people. It is not an option to completely remove humans from the shop floor in an attempt to stay at the forefront of innovation. Attempting to leap to full automation and the utopian “lights-out factory” does not work anyway, as automotive giants such as Ford, Chrysler, GM, and Tesla can testify. A significant portion of human employees will indeed need to give up their roles. On the other hand, improved productivity levels open up space to retain personnel and uplift them to more creative, managerial, analytical, social, or overall more enjoyable jobs. For certain tasks, humans still need to be kept inside the manufacturing loop. For example: • Complex assembly routines and handling of flexible components. • Large vehicle subassemblies contain many variable components and require more hand-eye coordination than one cobot can handle. Humans are needed to make sure everything lands in the right position while the cobot provides assistive muscle power. • Fashion, footwear, jewellery, art pieces, and other products where creation borders on artistry rather than mechanical assembly require the aesthetic eye of humans. People are also needed to spot aesthetic deficiencies in custom one-offs in order to correspond with customers before finishing the production batch. • While intelligent automation software can spot bottlenecks in efficiency, humans are required for creative problem solving and context-awareness to make decisions. A spirit of flexibility and innovation is just as important as the accuracy of perfect repetitions. 1.6 Mission: Install a Cobot Cobots have numerous advantages over industrial solutions or people-only workspaces. They enable faster, more precise, and more sophisticated operations while reducing downtime and maintaining employee satisfaction. Low-voltage operation and reduced material waste fits with sustainable innovation and corporate social responsibility programs. Many companies are reporting surges in production capacity and staff generally experience the presence of cobots as favorable. For example, industry leviathans like BMW and Mercedes-Benz are reaching the conclusion that in many parts of the production process implementing a cobot has been the right decision. Connecting all parts of the production line with full automation solutions is a pipedream. It works only when all steps are perfectly attuned, and in reality this never happens and one misstep can be catastrophic. Whether to hire a human, a robot, or a co-robot is a complex and ever-more pressing decision. Statistical process control is paramount for large organizations to make unbiased data-driven decisions. Determine the key performance indicators, then find the most critical bottlenecks and major opportunities for leaps in production efficiency, product quality, or staff unburdening. Talk to employees for their insights and probe their level of skill and enthusiasm needed for working with their new artificial assistants. Digital transformation should be an exciting shift in the organization and its people, so apply new technological advancements only where it makes sense. Despite common beliefs about robotization, the cobot is an entirely separate product category that can be a surprisingly plug-and-play solution for simple tasks, with programming apps becoming increasingly intuitive. A cobot’s flexibility makes it perfect to run early experiments to help companies find its best spot on the factory floor. Its unbelievable precision, consistency, and level of control generally can make a strong first impression on customers. Not only can cobots increase production capacity while reducing idle time and cycle time to accelerate manufacturing across many vertical markets, but they also enrich the work environment resulting in happier and more involved employees. For many companies, a cobot can be the next logical step in their digital transformation.

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Why Manufacturing Companies Must Consider Business Intelligence

Article | December 14, 2021

Do manufacturing businesses require Business Intelligence (BI)? The answer is YES. Manufacturing is one of the most data-intensive businesses, producing massive amounts of data ranging from supply chain management to shop floor scheduling, accounting to shipping and delivery, and more. All of this information would go to waste if not properly categorized and utilized. Scrutinizing and analyzing your data with business intelligence will help you become a more efficientand productive organization. Your organized data can show you where the gaps or inefficiencies are in your manufacturing process and help you fix it. Many companies simply are not willing to change or think they are done once they make a change. But the truth is technology, consumer demands, the way we work, human needs and much more are constantly changing. Michael Walton, Director, Industry Executive at Microsoft BI has the potential to improve the operations of an organization and transform it into an organized one. According to Finances Online research, more than 46% of organizations are already employing a BI tool as a significant part of their company strategy, and according to Dresner Advisory Services research, 8 in 10 manufacturers who use BI for analytics have seen it function successfully. How Manufacturing Operations Are Improving with Business Intelligence? As revealed by the BI statistics above, we can see that business intelligence is critical in manufacturing. To further illustrate how business intelligence supports the manufacturing industry, let's look at some of the business intelligence benefits that are making a difference in the manufacturing industry. Advances Operational Efficacy While modern enterprises create massive amounts of data, not all of this data is relevant. Today's business intelligence solutions take all of the data from your organization and transform it into an easily comprehensible and actionable format. It enables you to minimize or fix errors in real-time. Additionally, it helps you to forecast raw material demand and assess procedures along the supply chain to ensure maximum efficiency. Allows for the Analysis and Monitoring of Financial Operations Business intelligence solutions provide insight into sales, profit, and loss, raw material utilization and can usually assist you in optimizing resources to increase your return on investment. Understanding your cost-benefit analysis, BI enables you to manage production costs, monitor processes, and improve value chain management. Assists in the Management of Your Supply Chain Manufacturing companies engage with various carriers, handling these multiple processes can be complicated. BI enables manufacturing companies to have more accurate control over shipments, costs, and carrier performance by providing visibility into deliveries, freight expenditures, and general supplies. Contributes to the Reduction of Inventory Expenses and Errors Overstocks and out-of-stocks are substantial barriers to profitability. Business intelligence can assist you in tracking records over time and location while identifying issues such as product faults, inventory turnover, and margins for particular distributors. Determines the Efficiency of Equipment Several factors can cause inefficient production. For example, errors with equipment due to improper installation, maintenance, or frequent downtime can reduce production. So, to keep industrial operations running well, one must monitor these factors. Manufacturers can maintain their machines' health using data analytics and business intelligence. It provides real-time information about your production lines' status and streamlines production procedures. How Business Intelligence Helped SKF (SvenskaKullagerfabriken) to Efficiently Plan Their Future Manufacturing SKF is a key supplier of bearings, seals, mechatronics, and lubrication systems globally. The company posses its headquarter in Sweden and has distributors in over 130 countries. Due to SKF's extensive worldwide reach and product diversity, they constantly need to forecast market size and demand for their products to modify their future manufacturing. Generally, SKF experts developed and kept their forecasts in traditional and intricate excel files. However, the efforts of maintaining and reconciling disparate studies were excessively high. As a result, SKF used require days to generate a simple demand prediction. Later, SKF integrated its business data assets into a single system by utilizing business intelligence in production. Following that, they could swiftly begin sharing their data and insights across multiple divisions within their firm. They are now able to aggregate demand estimation fast and does not face cross-departmental issues about data integrity for the vast number of product varieties they manufacture. This intelligent data management enabled SKF to plan their future production operations efficiently. Final Words Business intelligence in manufacturing makes a big difference in the organization's entire operations. Given the benefits of business intelligence in manufacturing, a growing number of manufacturers are implementing it in their operations. According to Mordor Intelligence, Business Intelligence (BI) Market was worth USD 20.516 billion in 2020 and is anticipated to reach USD 40.50 billion by 2026, growing at a 12% compound annual growth rate throughout the forecast period (2021-2026). Hence, we may say that the business intelligence is crucial for manufacturing and is booming, thanks to its enormous potential and the numerous benefits it provides to various businesses. FAQ Why is business intelligence so important in manufacturing? Organization intelligence may assist businesses in making better decisions by presenting current and past data within the context of their business. Analysts can use business intelligence to give performance and competitive benchmarking data to help the firm run more smoothly and efficiently. What value does BI add to manufacturing? Business intelligence solutions provide insight into sales, profit, and loss, raw material utilization and can usually assist you in optimizing resources to increase your return on investment. Understanding your cost-benefit analysis enables you to manage production costs, monitor processes, and improve value chain management. What is business intelligence's key objective? Business intelligence is helpful to assist corporate leaders, business managers, and other operational employees in making more informed business

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Spotlight

ICCNexergy, Inc.

ICCN+Palladium is excited to announce that it is now Inventus Power. On December 11, 2015 we will deactivate this account. Please follow www.linkedin.com/company/inventus-power for all news and updates.

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