Unleash the Power of Factory Intelligence with Shoubii..

Progress is inevitable and eternal, and that is the apposite also for the ever-growing manufacturing industry which started as a purely man-made industry. People had started to specialize in different skills for manufacturing goods byand when the era of machines arrived. Then people progressed to specialize in skills for handling the machines that manufactured goods and depended on ERP tools to manage the manufacturing process and business functions that were involved.

The sector then proceeded to evolve to an age of machine integration that revolutionized human-machine interaction, automation of manufacturing processes and business functions. Technological advancements have made it convenient for manufactures to economically produce goods of higher quality more efficiently. This led to a surge in digital manufacturing solutions and tools competing to produce more efficient solutions.

SAP Manufacturing solutions is one such provider that has enabled companies to integrate and embed intelligence in manufacturing processes with a single-source of real time information as it can provide a fully integrated solution from machine level to ERP all-in-one. However, when it comes to technology one size doesn’t fit all, different manufacturers have different methods, materials, processes, speed and requirements. Who would not like a tailor-made solution where they can bend the way the standard processes are executed?

Shoubii Consulting happens to be the mother-lode of tailor-made solutions. The tools that we use to make this possible – SAP MII, SAP ME, SAP DMC, GE Proficy, Oracle Cloud, Apriso – are boundless. The skillset we possess is a banquet of SAP modules like SAP HANA, SAP IS Retail, SAP Fiori, SAP EWM and Oracle cloud solutions like ERP, IoT, SCM. When consumers are presented with a variety of options, it expands the possibility of having more user-friendly and sustainable solutions that require minimum post deployment support.

We at Shoubii work hand-in-hand with the clients to understand the requirements better. Having worked with multiple industries – like steel, aerospace, pharmaceutical, chemical – Shoubii has gained the experience and proficiency and has earned the reputation of consistently providing solutions on time and of superior quality. This was made possible as Shoubii is a bustling hub of activity, with an abundance of outstanding young individuals working to make a name for themselves and busy creating a long-lasting, successful history. Our presence piques the curiosity of our competitors. We are on a mission to make the process automation of the Manufacturing Industry simple, significant and comprehensive. Shoubii Consulting essentially revolutionizes user experience in the Manufacturing sector.

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Revolution of Next-Gen Autonomous Mobile Robots (ARMs)

Autonomous Mobile Robots (AMRs) are the next generation of industrial robots designed to work in a collaborative environment and can be used for different tasks to improve production and manufacturing flexibility.

Manufacturing flexibility improves a firm’s ability to react quickly to customer demands and increase production system productivity without incurring high costs and excessive resources. The emerging technologies in the Industry 4.0 era, such as cloud operations or industrial Artificial Intelligence, allow for new flexible production systems.

Autonomous Mobile Robots can work without human intervention, making them ideal for repetitive jobs such as welding, painting, assembly, and packaging. They can also be used for material handling and sorting, pick-and-place, machine tending, and more. ARMs can increase the efficiency of manufacturers by eliminating human error in repetitive tasks and by providing increased flexibility in how work is done on the production line. These robots can also be used as a mobile solution for companies that need to relocate their factories or warehouses.

In recent years, there has been an increasing demand for autonomous robots, and manufacturers are looking for ways to increase their production without hiring more employees. These next generation of robots will be able to move autonomously without being tethered to a power supply or a fixed location, allowing them to work in more places and for more extended periods.

Applications of Autonomous Mobile Robots

The following are some of the applications of autonomous mobile robots in the industrial industry:

As inventory and components fetch-and-carry workhorses: Workers do not have to waste time going long distances just to transfer parts required for production. Without jeopardizing worker safety, AMRs can execute the task just as well and swiftly.

A suitable alternative for conveyors: Parts must be transferred from one area of the manufacturing floor to another. AMRs can function as mini conveyor belts, allowing for easy transportation without the need for additional supply chain infrastructure.

Acts as a collaborative robot: AMR ensembles may be assigned to repetitive operations like welding and spray painting, which is very useful in hazardous environments. A robotic manufacturing arm mounted on an AMR may be moved around the production line to conduct collaborative jobs.

Inspection of difficult-to-reach parts: Manufacturers can attach inspection kits to AMRs as payloads to record and document equipment in dangerous or difficult-to-reach locations.

The most significant advantage of AMR is that it offers several navigation solutions. An AMR uses a pre-programmed map to navigate and plans its own paths to the destination. It can identify and avoid obstacles as well as maneuver around them. As a result, the AMR robot is more adaptable since it can adjust its direction dynamically and with less effort.

In spite of the perception that the AMR robot is more expensive, in reality, it could be more cost-effective due to its flexibility and ease of setup.

Leveling up with the help of Artificial Intelligence

By using artificial intelligence (AI), AMRs are able to learn from experience, adapt to new inputs, and perform similar tasks to humans. AI will play a key role in the setup and operation of AMRs, simplifying the deployment process and enhancing workflow.

Artificial intelligence combined with strategically positioned cameras that operate as extended robot sensors is helping certain AMRs take their smarts to the next level. Even before they reach a location, AMRs may learn to adjust their behavior using AI. This allows them to avoid high-traffic areas at certain times, such as when supplies are delivered and transported by fork truck regularly or when big groups of workers are present during breaks or shift changes.

Predictive Analytics: A Key Boon for Manufacturing

Predictive analytics is a powerful tool to help manufacturing companies make better decisions and improve efficiency. It provides a competitive edge for organizations in the manufacturing industry. It can help manufacturers identify new trends and opportunities and address challenges with an efficient solution.

Predictive analytics can forecast demand, manage inventory, and predict maintenance needs to minimize downtime. It is also used for quality control by identifying defective products before shipping. It is an excellent example of how data science can be applied to business problems to increase decision-making effectiveness.

Predictive analytics uses statistical techniques to identify patterns in data and use this information to make predictions. It is a powerful tool that can help manufacturing companies predict demand and make better production decisions. Accordingly, IDC estimates that spending on AI-powered applications, such as predictive analytics, will increase from $40.1 billion in 2019 to $95.5 billion by 2022.

Some advantages of predictive analytics

  1. Predict performance by detecting patterns

Predictive analytics can filter through massive volumes of historical data far faster and more precisely than humans. We can enhance output by 10% without losing first-pass yield by using machine learning technology to recognize recurrent patterns and other connection factors.

AI and machine learning can look for trends and combine them to assist your company in uncovering possible efficiency gains, foresee problems, and cut costs.

  1. Analyze market trends

Another application for PA is forecasting customer demand. Knowing what to expect in the future might help you determine what to do next.

Every business conducts some manual market research. For example, some consumer items are seasonal and sell better at certain times of the year. Demand forecasting may be aided by predictive analytics using statistical algorithms, which isn’t a new concept.

Customers’ future purchase patterns, supplier connections, market availability, and the impact of the global economy are all influenced by a variety of variables. The only way ahead is to manage them all through PA.

  1. Assists with inventory management

Supply chain management—stocking raw supplies, keeping completed goods, and coordinating transportation and distribution networks—is a complex commercial process that necessitates significant training, data from several sources, and excellent decision-making ability.

A computer model based on your data, on the other hand, may help supply chain managers make more confident and precise judgments. For example, such a model may ensure that you are never overstocked, understocked, or overburdened with unsaleable goods, even determining the best positioning of things on your shelves.

  1. Enhance the product’s quality

There are make-or-break steps in every manufacturing process where overall product quality is determined; these are frequently handled by humans who are prone to error. Artificial intelligence (AI) and machine learning are cutting-edge alternatives to this problem. Sensitive manufacturing stages can be delegated to robots that use machine learning to improve with each use. When compared to human-made items, this results in higher product quality.

PepsiCo, for example, has used machine learning systems to improve how it makes one of its famous Lays chips, from estimating potato weight to examining the texture of each chip with a laser system. These have resulted in a 35% increase in product quality.

Conclusion

Predictive analytics is undoubtedly a key boon for manufacturers as it can help them identify new trends and opportunities and address challenges with an efficient solution. It can also help manufacturers understand their customers better and create products that will be successful in the market.