IIoT

Connecting Industrial Protocols and the Cloud
admin
November 22, 2022
Big Data, Cloud Computing

Why Connect Industrial Protocols with Cloud

Industrial protocols are conversations between industrial automation products for data collection or control. At the beginning of industrial automation, communications were a competitive differentiator, and automation vendors developed communication protocols to leverage technical advantage and lock in their customer base. It has changed with time; today, vendors have extended their protocols and even designated them industry standards to boost adoption. Vendors acknowledged that suppliers with the largest ecosystem of products to choose from, would have a better livelihood of winning parts of a project, if not the complete project. Vendors also learned that it is challenging to be a specialist in all areas of automation. Let’s find out different industrial protocols and those that can be compatible with cloud applications.

Different Types of Industrial Protocols

With time, the manufacturing marketplace has become prevailing by a set of protocols, possibly from the leading suppliers of automation products. Before examining the best-suited for the cloud, let’s know some of the most common industrial protocols. These include protocols such as Modbus, Profinet, CC-Link, Ethernet IP, etc. Many of these are present in different forms to acknowledge varying topologies and purposes eg-dedicated wires vs. Ethernet.

Attempt to bring standardization over the years fetched technology from the OPC Foundation, which was originally Microsoft technology-based, using COM and DCOM Windows technologies for communications between applications. Hence, OPC (OLE for Process Control – OLE that is, Object Linking and Embedding – the technology after COM) is delivered.

1: OPC

OPC obtained standards for accessing data, either subscribing or polling, and the purpose of different data types and how to manage them (Analog and Discrete variables, History Data, Alarms, and Events, among others).

In time, this standardization endeavor shifted from windows technology-centric to operating system-agnostic to aiding Linux and delivering functionality that would be useful to Internet-based communications.

2: OPC UA

The new standard was recognized as OPC UA- with OPC now representing Open Process Communications and UA representing Unified Architecture, one standard to supersede the previous standards that had developed.

3: MQTT

Another technology that is more concentrated on the transfer of messages and less on the content of messages generated out of the need for a very distributed infrastructure with limited bandwidth, as found in the upstream oil and gas market. This protocol is known as MQTT. It is used in the industrial automation marketplace, specifically for cloud communications, and has become very popular in recent years.

4: BACnet

The vertical market shows unique requirements and has supported the requirement for unique developments. BACnet is the leading protocol in the Building Automation Systems (BAS) space. In the Power Generation and Distribution Space, several protocols like IEC-61850, 60870, and DNP-3.

Over time, these protocols have survived on various topologies, and today most of them offer Ethernet compatibility.

Why is the Cloud So Important?

The advantages of cloud computing are numerous and stimulating. They possess:

  • Transformation of capital expenditures to operational expenditures
  • No need to concentrate on infrastructure management
  • Benefiting a constantly scalable architecture
  • Furnishing accessibility to your absolute organization, anywhere and anytime
  • Benefiting services from domain experts (security, upgrades, solution development)

The cloud can endure different forms, from a solution delivery by industry leaders like Microsoft and Amazon to more scaled offerings for targeted markets. Ultimately, there are hosted solutions, pushing on-premise servers to virtual servers in the cloud, but fully controlled by the IT staff of the organization.

The objective of cloud computing is to provide a lower total cost of ownership by reducing expenses in system management and hardware ownership and the capability to take advantage of solutions offered by others. These third-party solutions are usually built for market purpose and provides multi-tenant capability, letting the service provider handle many customers whilst offering data and user isolation. The concept of cloud computing, specifically for the industrial marketplace, is still in its initial stage, and businesses are fighting with cloud connectivity and the idea of hosting their data to the outside world.

However, the benefits are convincing as it reduces operating costs, and domain experts have developed vertical market applications that require connectivity to the correct data. Additionally, service providers can utilize knowledge gained over their extensive array of customers and offer great value to an individual customer. So, the failure mode of a product in an environment can be predicted by learning about the failure mode in other environments. It helps in potential predictive analytics tuned by the results and anonymization of data from a similar ecosystem of users. While connecting to the cloud, evaluating which industrial protocols best suit the application is necessary.

Things to Consider When Connecting to the Cloud

The best attributes offered by cloud-based solutions fall into two main categories:

  1. Security ( including access security and cybersecurity)
  2. Transmission (the quality and reliability of data) 

Security is mainly managed using VPNs (Virtual Private Networks). It is an excellent way for bi-directional and ad-hoc communications as it is designed for remote troubleshooting. Using VPNs for ad hoc access, customers can use solutions to secure and broker access to endpoints in a very organized and controlled way. It includes approval processes, windows of access and time limitations, and extra levels of authentication. 

For information communication to the cloud, it is becoming more prevalent to utilize public-subscribe models and connection brokers to enhance security. Remote sites will share data to a tight and secure connection. The users of data and cloud applications will subscribe to the data through a broker, eradicating application knowledge of remote communication details that illustrate an exposure. Microsoft IoT Hub is the best example of this technology. 

Industrial Protocols for Cloud Connectivity

It is optional that all industrial protocols are compatible. Without knowing each protocol and determining if it can be integrated into a cloud, a complete solution to the connectivity issue is to add edge device technology. It will manage the communications to the IT and OT environment and the need for cloud data transfer. Their devices are now covering the market with specific cloud connectivity or a toolkit approach that can be eased their configuration. Most of them are designed with data transfer as their primary function, whereas others support data modeling, visualization, and analytics, in addition to data transfer.

Ethernet is also improving with time in both topology and performance. A more visible improvement is device synchronization and the power to shape traffic. These attributes and other things are Ethernet enhancement called TSN (Time Sensitive Networking). TSN promises the skills to prioritize communications on Ethernet and control traffic bandwidth.

Connecting Safely and Securely

With the expansion of industrial protocols in the market, it is now feasible and easy to connect virtually any automation solution to the cloud with complete privacy, directly or using edge gateways.

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admin
October 13, 2022
Artificial Intelligence, Technology

How can Artificial Intelligence Boost the Manufacturing Industry?

Today, most of the Giant industries, around 83 percent, believe that AI delivers better outcomes; however, only 20 percent have embraced this technology. It is pretty clear that a stronghold on the domain is important for successfully adopting artificial intelligence in the manufacturing industry.

Domain expertise is important for successfully adopting artificial intelligence in the manufacturing industry. Jointly, they form Industrial AI that uses machine learning algorithms in domain-specific industrial applications. AI can be potentially used in the manufacturing industry through machine learning, deep learning, and computer vision.

Let’s check out some of the critical needs in artificial intelligence technologies in the manufacturing industry to obtain a better picture of what one should do to keep the business up-to-date and seamless.

AI Is a Broad Domain

Artificial intelligence is not the correct way to describe all the technologies, and we’ll discuss that they have applications in manufacturing industries. AI is a big subject with different methods and techniques that fall under it.
There are robotics, natural language processing, machine learning, computer vision, and many other technologies that also need attention.

Keeping this in mind, let’s begin with artificial intelligence applications in the manufacturing industry. So here are some industrial uses of AI.

The Goal of AI in Manufacturing

Artificial intelligence studies how machines can process information and make decisions without human interference. The best way to understand this is that AI aims to mimic how humans think but not necessarily. We all know that humans are better and more efficient in performing certain tasks, and in certain tasks, they are not. The best type of AI is one that can think and make decisions rationally and accurately. The best way to explain this is that we all know that humans are not efficient enough to process data and the complex patterns that appear within large datasets.

However, AI can easily do this job using sensor data of a manufacturing machine and pick out outliers in the data that provide information about the machine that will require maintenance in a few weeks. Artificial Intelligence can perform this in a fraction of a human’s time analyzing the data.

Robotics: The foundation of Modern Manufacturing

Many applications of artificial intelligence include software in place of hardware. However, robotics is mainly focused on highly specialized hardware. As per Global Market Insights, Inc, the industrial robotics market is expected to grow more than $80 billion by 2024. In many factories, for instance, Japan’s Fanuc Plant, the robot-to-human ratio is approx 14:1. This reflects that its possible to automate a large part of the factory to reduce product cost, improve human safety and enhance efficiency.

Industrial robotics demands specific hardware and artificial intelligence software to assist the robot in accurately performing its tasks. These machines are specialized and are not in the business of making decisions. They can run under the supervision of technicians, and if not even, they make very few mistakes compared to humans. Since they make very few mistakes, the overall efficiency of a factory improves when integrated with robotics.

When artificial intelligence is integrated with industrial robotics, machines can automate tasks like material handling, assembly, and inspection.

Robotic Processing Automation:

Robotic processing automation, artificial intelligence, and robotics are among the most familiar. It is important to understand that this process is not related to hardware machinery but software.

It involves the principles of assembly line robots for software applications like data extraction, file migration, form completion and processing, and more. However, these tasks do not play very important roles in manufacturing; they are significant in inventory management and other business tasks. It becomes more important if the production operation requires software installations on each unit.

Computer Vision: AI Powering Visual Inspection

Quality control is the manufacturing industry’s most significant use case for artificial intelligence. Even industrial robots can make a mistake, though the possibility is less than humans. It can be a huge loss if a defective product reaches the consumer by mistake. Humans can manually monitor assembly lines and identify defective products, but no matter how attentive they stay, some defective products will always slip through the cracks. Therefore artificial intelligence can help the manufacturing process by reviewing products for us.

Adding hardware like cameras and IoT sensors, products can be interpreted by AI software to catch defects automatically. The computer can then automatically decide what to do with defective products.

Natural Language Processing: Improving Issue Report Efficiency

Chatbots driven by natural language processing is an important manufacturing AI trend that makes factory issue reporting and helps requests more efficiently. It is a domain of AI that specializes in mimicking natural human conversation. Suppose workers can access the devices to communicate and report their issues and questions to chatbots. In that case, artificial intelligence can support them in filing proficient reports more promptly in an easy-to-interpret format. It makes workers more accountable and decreases the load for both workers and supervisors.

Web Scraping:

Manufacturers can use NLP for an improved understanding of data collected with the help of a task called web scraping. AI can check online sources for appropriate industry benchmark information and transportation, labor, and fuel costs. It can help in boosting business operations.

Emotional Mapping:

Machines are quite poor when it comes to emotional communication. It is very challenging for a computer to understand the context of a user’s emotional inflection. However, natural language processing is enhancing this area through emotional mapping. This brings a wide variety of opportunities for computers to understand the feelings of customers and operators.

Machine Learning, Neural Networks, and Deep Learning

The three technologies used in the manufacturing industry are machine learning, neural networks, and deep learning, which are artificial intelligence techniques used for different solutions:

  • Machine Learning: It is an artificial intelligence technique in which an algorithm learns from training data to decide and identify patterns in collected real-world data.
  • Neural Networks: Using ‘artificial neurons,’ neural networks accept input in an input layer. The input is passed to hidden layers that increase the weight of the input and direction to the output layer.
  • Deep Learning: It is a machine learning method where the software mimics the human brain like a neural network, but the information goes from one layer to the next for higher processing.

Future of AI in Manufacturing

What will be the next role of artificial intelligence in manufacturing? There are so many thoughts and visions coming from science and technology. The most visible change will be an increased focus on data collection. AI technologies and techniques used in manufacturing can do so much work independently. As the Industrial Internet of Things grows with increased use and effectiveness, more data can be gathered and then used by AI platforms to improve different tasks in manufacturing.

However, with the advancement in AI in the coming years, we may observe completely automated factories and product designs made automatically with less human interference. However, reaching this point is only possible through continuous innovation. All it requires is an idea- it can be the unification of technologies or using technology in a new case. Those innovations alter the manufacturing market landscape and help businesses stand out.

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Energy Harvesting and IIoT- Sustainability for the IIoT
admin
September 19, 2022
IoT, Technology

Energy Harvesting and IIoT: Sustainability for the Industrial IoT

The world is encountering tremendous economic and ecological changes along with challenges. The futuristic technologies are all set to transform the outlook of Internet of Things (IoT). Today energy supply to millions of communicating devices is a key issue. 

On a large scale, renewable energies have become a major source of energy generation. Fields embracing solar cells that generate energy using sunlight or wind turbines dominate the landscape. This renewable energy for energy generation is also embraced on a small scale. This entire concept is called “energy harvesting.” 

Small energy converters harvest energy from light, movement, or temperature differences. These harvested energies are enough to power a wireless sensor and transmit data using radio. 

Energy harvesting for radio-based products that are already part of mass production includes four different sources:

  • Motion – the press on a switch, moving machine parts, the rotary motion of a handle.
  • Light– the sunlight coming inside a room.
  • Temperature differences – existing between a heat source like a boiler, radiator, or pipes and the environment and variation between day and night.
  • Electromagnetic field – a contactless coil in a cage clamp around a cable controls the meter and calculates the line current.

For each source, different energy converters with different power parameters are present. The energy generation type and the corresponding power yield determine the possible sensor applications.

Enhanced Sustainability:

With the introduction of energy harvesting technology, radio sensors are sustainable as they don’t require cabling or battery power. They are environment friendly as well as cut expenditure.

Replacing a single battery typically costs around $300 US dollars in an industrial environment. Though changing the battery does not consume much time, traveling to the site, locating the sensor, testing the device, and documenting the process increases the labor cost. It is believed that batteries have a good service life, but in reality, companies are often engaged in changing them within one or two years to avoid early failures.

Today, resource-saving and environmental protection are the top priority. The rising cost of copper, the presence of harmful components, and battery safety are some serious issues. Wireless energy harvesting sensors are the best solution that considers both the financial aspect and environmental protection.

In Process for The Industry:

Sensors play a key role in industrial production. They can be used for quality and process monitoring or condition-based maintenance. A wide range of applications is developing in the direction of an industrial Internet of Things (IIoT) with the increasing usage of wireless sensors. Integrating energy-saving radio with local energy converters,battery-free and maintenance-free sensors can be installed directly on moving parts or in hermetically-sealed environments. For instance, it can be implanted to know the position of moving parts, power consumption, temperature of moving parts, liquids, or gases.

Sensors in Quality Control:

Quality monitoring manages the entire production process and ensures the desired properties of the end product based on different parameters.

For this purpose, environmental factors like temperature, humidity, and air quality or process factors like position or temperature are monitored.

Automated monitoring systems require data generated by sensors; for this purpose, sensors must fit seamlessly into existing production processes. Additionally, they must not need special training or generate follow-up costs in the ongoing operation. Therefore the integration of self-powered and maintenance-free sensors provides benefits.

Condition-based Maintenance with Battery-free Sensors:

Besides products, machines also need proper monitoring to ensure a seamless production process. These are prone to high wear, so it would be best to identify problems as soon as possible and take appropriate actions to maintain continuous quality assurance and protection against production downtime.

A primary problem with maintenance planning is the calculation of the intervals between each maintenance cycle. Normally, the interval between two maintenance dates must be as short as possible to detect deviations before any mishappening occurs. Still, each maintenance involves high costs for personnel and idle machines.

It is often possible to derive valuable information by closely examining a few simple parameters. For instance, a temperature rise can indicate higher friction, thus resulting into wear. Wireless temperature sensors can be installed for measurement processes. Humidity sensors monitor water leakage to prevent water damage. Temperature and humidity sensors also inform about air conditions and guarantee good air quality. That is why wireless energy harvesting sensors are best for various industrial applications. They are low maintenance, flexible, and within budget to install.

That is why wireless energy harvesting sensors are ideal for various industrial applications. They are maintenance-free, flexible, and inexpensive to install – outstanding features for assuring high-quality standards and greater sustainability in the Industry 4.0 environment.

IoT in the Factory Building:

IoT allows significantly efficient, adaptable, and individualized production in manufacturing. Using sensors networked with a smart IoT platform, it is now possible to develop a digital twin, i.e., an exact virtual image of a machine throughout its entire life cycle. Digitalization is becoming a part of buildings and will revolutionize them by providing automated service processes in facility management, higher energy savings, and better individual well-being for users. One important thing for factory buildings and industrial processes is battery-free wireless sensors.

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How is IoT Helping The Procurement Team in Improving Productivity
admin
May 13, 2022
Artificial Intelligence, IoT

How is IoT Helping The Procurement Team in Improving Productivity?

Today, almost every device is connected; whether it is your smartwatch, air conditioner, or television, we can say it’s a world where devices are more connected than people. No, doubt these connected gadgets present around us make our lives easier by working systematically. This is possible because of the most popular concept known as the Internet of Things, which can also influence the procurement team.

IoT, a.k.a Internet of Things, can be defined as a network of interconnected computing devices, either mechanical or digital machines. This technology allows transferring data without human-to-human interaction or human-to-computer interaction. Communication is possible using networks and cloud-based systems.

An IoT ecosystem includes web-enabled smart devices that collect, send and work on data collected from their surroundings utilizing embedded systems such as CPUs, sensors, and communication hardware.

IoT devices can exchange sensor data stored in the cloud for analysis purposes or examined locally by interlinking to an IoT gateway or other edge devices.

Besides this, these gadgets can connect with other related devices and respond according to the information they receive from one another. Even individuals can operate the devices for the beginning setup, give instructions, or recover data; the device can perform most of the tasks without human interference.

The Role of IoT in Procurement

Procurement is an important part of the business. It demands the implementation of new technologies to boost productivity, enhance customer service and save costs. As of now, the procurement process is also embracing automation; IoT in this process is one of the most exclusive things happening in the era of digital transformation.

The inclusion of the Internet of Things will provide greater spending visibility and understanding of the supply and equipment used for the procurement process. So, with a proper understanding of what is being used and the requirement specified, the procurement team will have access to optimize catalogs and manage expenditure. Forecasting demands more closely using analytics can significantly improve budget and contract management. This also helps in improving budget and contract management. Despite this, the data generated through IoT sensors and other devices can assist in making informed decisions.

Let’s know how IoT works in procurement.

Traceability of Materials:

A study done by a McKinsey Global Institute shows that by the end of 2025, the Internet of Things’ possible contributions to inventory management, logistics, and supply chain management would reach 560 billion to $850 billion per year. This shows the possible IoT-oriented future awaiting us. Most of the time, IoT contributes to these sections by tracking. IoT sensors can help in making inventory management systems more effective.

For instance, RFID tags connected with IoT devices can track physical inventories and eliminates the need to scan barcodes or labels. In fact, businesses with vast inventory can track the days before items expire using interlinked IoT devices, saving the business from huge losses. IoT also prevents product theft by enabling businesses to know the location of their products.

With the use of machine learning, procurement teams can manage products per demand.

Supply Chain Visibility:

In this process, the procurement team can also potentially use IoT technology. Supply chain visibility, items are documented as transported from the manufacturer to the customer. An IoT-enabled system can read data from various devices like smart tags and sensory data like surrounding temperature and humidity, vehicle speed, and geolocation and accordingly follow the supply chain when connected to it.

The adoption of IoT devices to track inventory and route planning provides the details about where and when items are delayed in transportation. This allows emergency planning and identification of other options to accelerate the supply chain.

Stock Management:

Along with smart shelves and storage bins that inform about the stock levels in real-time and how long the product has been on the shelf, IoT also assists in detecting the pattern of consumption.

For instance, if a product named X is on shelf A and has been the quickest utilized item, IoT sensors will monitor the usage rate and suggest its economic order quantity (EOQ).

This clears how essential procuring an item is, which products are needed, and what amount. Procuring the right inventory quantity reduces costs by lowering waste and the menace of shortage.

Monitor and Alert Maintenance:

The sudden breakdown of equipment in a production unit is the most horrifying dream as it disrupts the business. If the condition of the equipment is not known, things become more difficult and result into process disturbance, indefinite downtime, and even business loss. Regular monitoring of the equipment’s condition through IoT sensors permits the team to watch indicators like vibration, oil, temperature, and performance.

When these indicators go out of range, the sensor alerts the team via computers.

In fact, smart sensors also alert when a machine’s working pattern changes or is about to fail. So this allows teams to schedule the maintenance, decrease the chances of sudden machine failure, and ensure seamless productivity.

Better Decision Making With Predictive Data Analytics:

Procurement teams can predict the future using predictive data analytics and spend analytics. These predictions assist in making critical decisions for designing and executing business techniques. Continous flow and accumulation of data with IoT devices also help create more robust and relevant historical data.

Infact, joining IoT data with additional data coming from other sources can boost business growth.

For example, knowing what quantity of a product is needed can help send accurate requisitions for approvals and create error-free purchase orders.

For example, having information on what quantity of a product is being used can help in sending accurate requisitions for approvals and generating error-free purchase orders. This results in an efficient and effective purchase management system. Data collected by IoT can also be used for onboarding suppliers with supplier management solutions to get new products based on previous performance metrics and set criteria.

IoT Procurement Takeaway:

The Internet of Things has become a sensation and is impacting almost every industry. So, it will be smart to invest in this technology and unheave the existing business model.

The procurement team requires a comprehensive IoT framework consisting of machine learning, artificial intelligence, and embedded technologies. These technologies, all together, can bring holistic change and offer maximum benefit.

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How can IoT Sensors Improve Productivity in Manufacturing
admin
April 18, 2022
IoT

How can IoT Sensors Improve Productivity in Manufacturing?

Internet of Things has been reaching out to almost every sector, and as a result, it is expected that the global IIoT market will reach $103.38 billion by 2026. Today IoT devices are more affordable, and many manufacturers invest in smart factory technology. One of the significant parts of smart factory technology is IoT sensors. It is essential to gather the necessary information and send data to the cloud for analysis in manufacturing. Businesses analyze data collected from the sensors to produce the most fitting solution to enhance productivity, avoid unplanned downtime, and cut manufacturing expenses.

IoT Sensors

In the Industrial Internet of Things, sensors are able to detect different types of external information and change it into data or signals that humans and machines can comprehend. Data is stored in a database which is managed either on the cloud or within the building for processing and analysis. 

IoT sensors employ different types of technology like optics, infrared and thermal to catch the required information. Sensors can also collect one or many kinds of data. Sensors include measuring distance, levels, pressure, environment changes, or anomalies in production line batches.

Types of IoT Sensors

Vision Sensors:

Images are caught by a camera and processed using software to know parts’ presence, orientation, and accuracy. Adoption of vision sensors ensures product quality and consistency throughout batches. It is used chiefly on automotive, food and beverage, and general manufacturing production lines.

Proximity Sensors:

This sensor is used to calculate the distance between two objects. It is used primarily in manufacturing, where machines must know distances between products or measurements for assembly robots.

Pressure Sensors:

This sensor is used to measure the pressure of fluids or gases in an industrial environment. It is vital to maintain the correct pressure for the product quality or safety of the crew.

Temperature Sensors:

The temperature of the component indicates if they are failing or overheating. This can allow the maintenance crew to replace the fault before it results in expensive mechanical failure. Temperature sensors also monitor the ambient temperature to assure the quality of the product or food safety. Instant alert of a cooler going over-regulated temperature helps in saving the unplanned cost of food waste.

Humidity Sensors:

Balanced moisture can be an essential factor contributing to the final product quality. Monitoring the moisture guarantees that quality standards are always fulfilled. 

Humidity also degrades equipment, so this sensor can inform the team if the humidity level gets disturbed. It is crucial to maintain the required moisture to enhance sensitive equipment’s life. 

Level Sensors:

Level sensors alert the team if the fluid or solids level goes down. In this way, it ensures that hoppers are filled before they run out, and production time is not lost.

Acceleration and Vibration Sensors:

It is crucial to monitor the movement of equipment to know the accuracy or need for machinery maintenance—excessive vibration in the machine indicates loose bolts or worn-out bearings or motors that are about to fail.

Sound Sensors:

The pitch of some machinery also indicates whether it is operating correctly or not. By observing the machine’s pitch, the maintenance crew can be informed if the machine is running too high or low and needs repair or replacement.

With the evolvement of IIoT technology, major industrial sensor manufacturers are designing “smart” sensors. These sensors are easy to implement than analogue ones (as it requires PLCs to process and interpret data protocol). A smart sensor is able to process data within the sensor and transmit it directly back to the managing platform. This causes data transmission to be more versatile and saves bandwidth by just sending helpful information.

IoT Sensor Connectivity

IIoT deployment may involve a few or thousands of sensors monitoring and controlling a single machine or an entire production line. Sensors need to be connected to send back the data to the network and cloud software. This connection can be wireless or wired, and each of them comes with some form of pros and cons. 

Many manufacturing plants opt to hardwire their IoT devices using industrial Ethernet cables. Hardwiring can guarantee a reliable connection, but the distance between sensors, I/O blocks and PLCs can limit its function. There is also the risk of damage to the cable, which comes with the cost of replacing it. 

Nowadays, wireless IoT sensors are in trend as wireless are more powerful and reliable. It can cover a much larger area and distance. It is more scalable as many sensors can be deployed through this. 

For instance, a single private LTE network can wirelessly connect many devices on a factory floor and provide seamless functioning.

How Are Manufacturers Improving Productivity?

Here are some examples that prove that IoT sensors play an essential role in helping manufacturers save costs and improve productivity.

Enhanced Product Quality:

In machines already connected to the cloud platforms, it is easy to store data such as temperature and pressure to track in production batches digitally. Machine vision via high-resolution cameras is another way of tracking products through a production line. Vision sensors with software can monitor product quality. Hence, this technology can reduce poor-quality products from reaching consumers who can imperil the company.

Minimize Unplanned Downtime with Predictive Maintenance:

The accessibility to real-time data and cloud-based analytics allows engineers and maintenance crew to spot inefficiencies in machinery. It is more valuable than scheduled maintenance, in which programs can analyze data collected from sensors to predict if an unplanned breakdown will occur or not. This ultimately helps technicians replace components before they fail, dodging any accident or expensive repair.

Warehouse Management and Asset Tracking:

In a smart warehouse, the IoT sensors can help track the flow of assets throughout the factory. Autonomous robots can pick or move or pack orders without human interference. Automating these tasks can allow employees to focus on other priority tasks.

Improve Procurement and Forecasting:

Sensors can also be helpful for procurement managers. Sensors installed on the production line can watch the assembly of products, help control raw materials usage, and reduce waste. It also alerts the crew when the supply goes down. Thus monitoring these essential items using sensors can reduce waste and enhance forecasting.

Product Development:

We all know that product development is one of the most critical and costly processes in manufacturing. Manufacturers can reduce the sum and make a better decision before concluding on total production.
One of the best ways is to gather data through sensors on the production floor and advanced manufacturing analytics to reduce the time consumed in the R&D process.

In fact, sensors on products can be implemented to collect data in real-life scenarios. Collecting data in real-time allows engineers to make rapid changes to get a more efficient product.

Summary

It is apparent that sensors plan a crucial role in daily operations throughout factories. Data collected using sensors can help develop a more efficient production line, machine operation, and safety.

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How do Cellular Networks in IIoT Promise Scalable and Secure Connections
admin
March 2, 2022
IoT

How do Cellular Networks in IIoT Promise Scalable and Secure Connections?

Internet of Things has been an exclusive topic to be discussed for the last few years. We all know about the opportunities it unveils in business. How adopting this technology can add more benefits and success to the company. But do you know how the choice of connectivity can affect the performance of the solution offered by IoT? One must consider the network, its effective range, reliability, device battery use, how much data of different types it can transfer, and the speed for implementing Industrial IoT projects.

Many connectivity options are available, and cellular connectivity is the most popular as it is a simple, scalable, and secure way to connect industrial IoT devices.

Today manufacturers all around the world are stepping ahead to make their business competent and more efficient by integrating it with IoT applications as it can boost productivity, reduce equipment downtime and enhance the efficiency of factory operations and processes.

Cellular IoT networks and devices are cheap and widespread, alluring more interest. Many organizations have already deployed cellular IoT networks to cut out the different business problems and start smart manufacturing. Organizations establish connectivity to gather data from various devices to adopt these projects successfully.

Cellular Connectivity In Industrial IoT Application

Integrating connected devices with cellular connectivity has been a long-time attempt of industrial engineers in creating autonomous manufacturing equipment and factory automation systems. Mobile technology has offered the skill for organizations to seamlessly accelerate the speed and extend the data processing capability of the systems.

Cellular connectivity empowers companies to transmit and process large amounts of information in a jiff without the requirement to send all the data through a centralized IT infrastructure. This provides organizations with an opportunity to execute strategies for machine health monitoring with the aid of wireless industrial IoT sensors without any requirement to construct their infrastructure.

Influence of Different Cellular Standards on IoT Connectivity

Cellular connections are pretty flexible with different protocols. Mostly LTE, i.e. Long Term Evolution is the prevalent worldwide approach. IIoT service providers prefer it because of its lower cost, ease of implementation quality, and less power need.

Device vendors are launching new cellular IoT devices, gateways, IoT inclined routers and new solutions that fit into IIoT solutions like IoT apps, IIoT system integration, and device analytics.

Including cellular connectivity to extend IoT solutions will boost the range of Plug and Play Sensors applications, enhancing the efficiency of Industrial IoT roll-outs and fast reconfigurations to fulfil the business requirements. Robust connectivity is necessary to achieve critical information about the health and performance of the machines; hence industries are focusing on getting the latest technologies that provide faster and more precise information. For successful deployment of cellular IoT systems, solution providers and multi-national end-user companies seek solutions that offer worldwide support (2G, 3G, and LTE). These are already becoming part of businesses scaling IoT solutions and assuring seamless deployment worldwide.

eSIM

Cellular standards impact the performance, range, ease of development, reliability, security and cost of implementation for expanding IoT in the manufacturing industry. Traditional sim cards which are utilized in cellular IoT devices are confined to single network carriers. They need a technical to manually insert or replace sim cards which cause deployment bottlenecks, especially in remote locations.

These challenges can end with the latest eSIM platforms, which have a non-removable chip that can download the carrier profile over the air and permit multiple telecom providers to programme in advance so that the device can choose the best connection.

IoT devices with eSIM have a single sim card with a cellular module that offers the ease of deploying anywhere globally and guarantee dependable connectivity due to their ability to switch carriers without any need for physical human interaction.

These devices are a blessing for monitoring machines in complex and remote areas and help to slay logistical challenges during movement. All these features provide speedier scalability for IoT applications.

Benefits of Cellular IoT Connectivity

Today, cellular connectivity is attaining unexpected height for implementing integrated machine-to-machine communications that facilitate wireless condition monitoring of industrial assets. This is all possible because Cellular IoT connectivity enables high network dependability. The cellular IoT devices data (transfers with high data rates) are not disturbed by bad weather conditions. The distance between the device and the base location does not impact it compared to other wireless communication options. This shows that cellular connectivity provides the best coverage and the capacity to avoid overload problems. It also offers greater freedom of mobility that supports obtaining connectivity even in complex environments where equipment is not stationary. 

Mobile technology impressively transforms Industrial IoT applications and solutions because of its advantages. In IIoT, various manufacturing verticals will keep using cellular IoT devices as the most successful implementation.

Digitalization

Digitalization of manufacturing operations guarantees lowered downtime & enhanced productivity, and cellular networks are essential to accomplish it. Cellular networks provide organizations with the opportunity to use these technologies to speed their Industry 4.0 journey potentially.

The availability of cellular network coverage eases the work by making it prompt and cost-saving for manufacturers to keep a watch on industrial assets even in remote areas. The incoming of 5G provides a more robust opportunity for organizations to leverage data through faster connections, ultimately improving capacity to handle real-time information to discover the most fitting and highly potential Industrial IoT.

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admin
October 19, 2021
IoT

How Can IoT Provide a Truly Effortless Experience?

IoT and IIoT have become a part of almost every industry. Their incomparable contribution to the growth and success of the services or products is remarkable. In fact, features offered by IoT and IIoT for customer service or field service experience have opened opportunities to boost customer loyalty to an exceptional level and have launched a new prospect for revenue generation.

However, the biggest challenge prevails in how to transform IoT advantages into an effortless experience.

The principle of the Effortless experience, described in the book by Matthew Dixon, has changed the concept of customer experience and shares what results in loyal or disloyal customers. The books share that

“Loyalty is driven by how well a company delivers on its basic promises and solves day-to-day problems, not on how spectacular its service experience might be. Most customers don’t want to be “wowed”; they want an effortless experience. And they are far more likely to punish you for bad service than to reward you for good service.”

The benefit provided by IIoT is visible across all industries, and it manifests itself in various forms for various applications. For instance, industrial production abilities enhance maintenance efficiency and labor safety, streamlining production and operational resilience.

Yet, IoT is not just meant to stay as technology but is about developing solutions that can deliver expected results for businesses. The value of field service organizations is rising day by day for operations. The service experiences offered by your technicians will imprint a lasting impact on your customers. It will determine the overall impression of your brand and will influence satisfaction, retention and future sales in a positive or negative way. Along with the delivery of notch-top services, customers expect effortless services too.

So, this makes it elementary to reexamining the way your organization provides services by resolving the complexities of the past and moving towards a future promising an effortless experience.

Concentrate on Effortless:

Is it possible for you to maintain the conversation when customers ask a question via one channel and then use another to ask for an update? Customers often expect history and context to be carried into future interactions regardless of how or when the conversation started. Yet many organizations still struggle and deploy different teams for various service channels.

Integrating the power of a centralized service console such as Salesforce Service Cloud with real-time and adding historical IoT telemetry from a Digital Twin will ease your teams’ work by providing full transparency, assuring context and history are available, 24*7. Besides, your team can carry diagnostics tests remotely by directly accessing historical data and cases along with service contracts plus KPI’s.

From effortless to predictable:

Advanced analytics tools and connected products have transformed the concept of knowing your customers, their assets, and equipment. Today, it is easy to acquire tones of relevant data that empowers you to predict the requirements of the customer even before they experience the problem.

Though the information is available but unfortunately unavailable to service teams within their operational tools, a no-code platform to utilize the power of IoT within their service console could be the best solution. This can proactively launch customer service operations to achieve an unparalleled level of customer and field service.

Make Simple Your Differentiator:

Delivering an effortless service can also assist in discovering new growth opportunities via AI/ML insights, which can contribute to great success. It can also boost operational efficiency by modifying the way you connect people, data, and devices using automated workflows and inventory management tools. Besides, risk can be minimized by effortlessly securing your organization, network, and people by identifying oddities and vulnerabilities to connect with confidence.

Finally, improve the user experience by providing differentiated and personalized effortless experiences to increase customer retention and business.

It is apparent that customer service organizations have been endeavoring for years to accomplish short wait times, excellent first-call resolution, and stretched support hours. Competent customer service programmers are not limited to these but also offer access to experts.

Above all this, customers have to be aware of their needs and where to look for a solution. Latest studies have found that organizations that can predict customer needs and make information availability easy are appreciated for excellent customer satisfaction. Additionally, customers are demanding self-service and want it to be effortless.

Conclusion

We all know that to provide an excellent level of customer service, it is essential to predict the needs of the customers before they encounter issues. Adding a no-code platform within their Service Cloud or Field Service environment can be helpful for your team.

We can easily conclude that an effortless experience for customers can be possible only by potentially utilizing IoT within the cloud service. By integrating the power of a centralized service console enriched with real-time and past IoT data, your team will enjoy complete transparency, assuring the context and history of customer contacts are accessible at any time.

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How did digital power contribute to the IIoT revolution?
admin
October 6, 2021
IoT

How did digital power contribute to the IIoT revolution?

Today, it is not a new thing if we provide digital controls to power supplies. Still, today many market drivers combine it to stimulate adoption across a surprising range of industry segments.

Advantages of Digital Power Emerge

Digital control in power supplies is an expanded sector; it includes essential digital signalling (like on/off) to an old analogue controller to complex operations, including a digital signal processor.

The latter represents an added cost; swiftly reducing chip price points and frequently sophisticated demand from manufacturers means that adoption is skyrocketing.

We can see the clear benefits of fully digital power supplies because of their much-advanced flexibility. The feasibility of adjusting power supply performance characteristics depending on different applications, environmental factors, and system performance variables expands the scope of practical benefits and cost savings.

Latest microcontrollers with DSP can examine the output voltage of every switching cycle, monitor fault and status conditions, react to warnings, and event logging is all possible options that would need hardware replacement earlier.
Today, when there is an increase in IIoT device demand and deployment, often in an application where physical access seems to be a challenge, this flexibility is powerful.

Besides, the location of many such devices on the network edge makes the value of real-time monitoring at this level valuable for multiple reasons, with predictive maintenance and enhancing efficiency.

IIoT value depends on data

Industry 4.0 of Smart Factory manufacturing applications are fit for digitally controlled power supplies. In smart factories, detailed logging can be integrated with other data in AI tools or dashboards to assure those performance parameters are managed in real-time. Another benefit is the ‘data lake’ of historical performance data can be extracted from these logs, facilitating predictive and preventative maintenance modelling to be highly improved. 

Programmable, Ruggedised Power Demand

The digitally programmable ability becomes necessary in ruggedized components and their designed operating environment, increasing product lifetime and better energy consumption.

Optimizing energy consumption by mapping and coordinating the power supply performance to the system power budget of particular value in extreme conditions, where thermal variations may influence standard performance.

As a result, not only IIoT enterprises are actively interested in digital power supplies, but recent reports share that global military requirements are increasing rapidly, and the reason behind it is digital power management.

Military and Telecom

One report released by Transparency Market Research predicts that the global next-generation military power supply market would reach up to US$ 20,111.7m by 2026, growing at a CAGR of 5.2% during the forecast period (2018 to 2026). As per TMR analysis, the programmable power supply segment occupies the maximum market share, increasing at a CAGR of 5.5% through 2026. Though there are many applications of programmable power supplies in the military, one fundamental purpose is to secure militarily significant sensitive electronic devices from grid power quality instability – whether everyday environmental factors or malicious actors cause that instability.

The telecommunications industry is another important growth market for digitally programmable and ruggedized power supplies as it needs robust and rugged power supplies that can be installed in towers. These towers encounter different challenges like high-salt marine environments near the cost to dusty city locations. It is essential to keep maintenance costs to a minimum to manage margins, particularly when viewing the new expenses of 5G network upgrades.

Implementation Advantages and Tips

A vast spectrum of applications and environments are leveraging from a digital power management solution, so it is a complex task to narrow down the field for a specific application is critical. The topmost benefits of digital power management are reduced cost and number of components, enhanced development time covers, and an enhanced number of DC-DC converter options. These are appealing features, but it also drags design challenges. Few considerations include general power supply design needs like overcoming unwanted ripple and managing direct current resistance (DCR), along with digital power management difficulties, precisely control algorithms, and firmware design. In fact, we can say that these have been the reason behind delayed digital power management implementations. The control algorithm is of central importance. Though it can be optimized and updated later, adequate expertise must be introduced early in the design process. 

Stability is one of the central design challenges which compelled analogue systems to get into a series of costly premium techniques. 

Digital power management systems can resolve this issue while offering compensation-free power converters with high bandwidth and enhanced transient response. This is possible by generating a completely synthetic current control loop that produces cycle-by-cycle phase current balancing. This process is essential for complex multiphase power supplies for significant CPU, FPGA and ASIC arrays that are generally used in rendering and artificial intelligence (AI) operations.

Through Digital power management, it is possible to control and monitor every setting through software, making designing and tuning loops more straightforward. The most valuable part is during debug time, the status and condition of the power supply become immediately apparent. Furthermore, the consequent strength to alter filters and neutralize the noisy conditions in software and near-real-time offers versatility in resolving any specific difficulties that come up and even accelerates the process.

Lastly, as the power supply should be functioning at an optimum level which implies that thermal performance should be excellent, in many cases allowing cooling provisions like airflow and heat sinks need to be optimized or even omitted. This leads to a slender design that can be suitable for restricted spaces and cabinets.

Future: Analog and Digital Combined

It is now apparent that digital control of power supplies is acquiring good attention across the board. There is an extensive list of benefits, from improving flexibility and reducing operating costs to increasing lifespan and integrating with broader IIoT strategies such as predictive maintenance and modelling. Even if analogue control has a role in low-power and manageable applications, the whole process will be digitized in the coming years.

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Generating Continuous Value for IoT Using Ecosystem Approach
admin
July 13, 2021
Digital Transformation, IoT

Generating Continuous Value for IoT Using Ecosystem Approach?

The emergence of the COVID-19 pandemic disrupted almost all sectors. Still, on the other hand, it opened a plethora of opportunities to improve the existing business culture by showing us the path of Digital Transformation. Today, the industry stands on the doorsteps of its much-awaited renewal. It is evident that manufacturing leaders have to adopt digital transformation but have to accelerate innovation while managing crucial processes like enhancing capacity without compromising product quality.

Thus, digital transformation is the new focus in the manufacturing industry, and no doubt, effective collaboration will be the best way to keep both things smooth and productive at the same time. However, this will not be easy as workforces have gone and are still mostly remote.

Pandemic Impact:

As the virus blanketed the globe, it became pretty clear that there would be a fight for survival among industries. There would be winners and losers. Before the pandemic situation, the manufacturing sector had been slow in adopting the digital transformation and lacked a data-centric mindset that has already transformed other industries. Even those who embraced multimillion-dollar Industry 4.0 or IoT initiatives were not receiving any excellent results to showcase their efforts. Unfortunately, when the pandemic knocked the globe, resources to support implementations went at the edge.

Not just they lost the data they needed to adapt at the moment but also potential value..

Digital Transformation:

Today the most asked question is why invest in digital transformation at the corporate level when there is no usable data from the factory floor? 

Well, Smart manufacturing does not demand to have an entire organization devoted to its success. In manufacturing, it can begin with capturing insights from the very initial operation- the machine assets that make products and people handling the machine. The assets are one of the most significant capital investments for any manufacturing industry, and it produces thousands of data points every second. Still, these valuable data are not captured and analyzed to improve the efficacy leading to no improvement or growth. Today’s factories are based on manual processes that result in massive inefficiencies and disturbs every part of the organization.

Insights along with correct action-driven from this data can lay the foundation for manufacturers to grow their business and stand above the competitors. Even the chances of errors and inefficiency are negligible.

Machine Data Infrastructure:

As we already know, there were many manufacturers, organizations, consultants and system integrators who attempted to rebuild the machine data infrastructure from scratch and produced varying degrees of achievement as a part of large IoT initiatives.

Even while leveraging a horizontal IIoT platform, the whole setup requires months or years. Once it is completed, the mechanism for capturing and contextualizing machine data has to build, and it needs regular maintenance. Not only are the expenses of sustaining these solutions limit, but the missing opportunity and value affiliated with misallocating resources to produce something that already exists causes a competitive disadvantage for the manufacturer.

Accurate real-time data automatically collected and transformed from machine assets produce a solid base for driving bottom-line value. When joined with visibility and actionability via alerts, analytics and automation triggered by the data, one can observe a 15-20% improvement in utilization performance in months.

Once this is over, the value achievement can be fast and multi-directional by integrating the data into other siloed data on enterprise factory and industry systems, i.e. from product designing to production, product quality, maintenance and logistics to run endless automation and accomplishment of exceptional value.

This enables an ecosystem of manufacturers and partners to speed up value attainment and reduce the risk of initiative failure by optimally adjusting the entities having individual skills, in particular IIoT initiatives.

IIoT Ecosystem:

IIoT Ecosystem includes manufacturers, machine builders, machine builder distributors, technology and solution providers, service providers, software providers, system integrators and consultants. Each has its unique skill, expertise, or intellectual property that can be used to drive a successful IIoT initiative. When the resources mentioned above are disarranged or sub-optimized, IIoT initiatives fail to deliver on the insured value proposition or fail entirely.

So, the question is, where should the manufacturer focus? Analytics, including both Machine Learning and Artificial Intelligence algorithms, can be developed and applied at the edge as well as in the cloud using analytics technologies. The correct alignment of skills and technologies produces the optimal formula for the manufacturer’s speedy and regular value generation.

Successful IIoT initiatives need selecting the right technologies and perfect alignment of the different entities in the IIoT Ecosystem that participate in the industry. In the IIoT Ecosystem, the alignment should be done based on each participant’s unique technology, IP and domain expertise to extract maximum benefit and reduce risk.

The emphasis should be on quick data transformation, excellent application, integration and automation into other best factory systems.

Pivot, Respond, Adapt:

As I already shared that many manufacturers suffered a lot during the pandemic times, and no doubt much of that suffering was out of their hands. But who were the ones who surpassed all the challenges and succeeded? Who were winners when the whole world was encountering losses at different levels? Well, the organizations that can pivot, respond and adapt at the tough times. It wasn’t easy, but they were prepared with the data, the tools and the mindset to win.

For manufacturers who had to spend a lot on difficult-to-implement should pump the breaks in favour of vertical solutions that can benefit immediately.

It’s time to switch to the new world of digital transformation. Are you ready for it?

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admin
December 31, 2019
IoT

Is IIoT is the Fourth Industrial Revolution?

Industrial Internet of Things (IIoT) is the next revolution which has finally entered the industrial world and made a recognizable impact on the market. It has permitted the manufacturing industry to digitize its overall business.

Most of the large scale manufacturers know about this highly-profitable revolution but still lack the knowledge for where to concentrate, put efforts and decisions to make initiate.

The ultimate objective is to drag in IIoT in manufacturing to shorten the downtime of factories, save energy through smart power saving and enhance the yearly revenue. The revolutionary Internet of Things can modify the manufacturing ecosystem by extending the value chain, moving toward the flexible production process and improving customer service. If your products aren’t smart even then get IoT Development Services.

What is the Industrial Internet of Things?

The IoT has influenced the sectors in a way that it is no more an unfamiliar word to any of the industry. The invincible qualities and benefits of IoT have knocked on the door of the Industrial and Manufacturing space to make way to modern revolution i.e Industrial IoT.

IIoT, along with different technologies like machine learning, sensor data, big data, M2M communication and automation would endeavour to transform the outlook of the existing manufacturing process while achieving the best outcome.

What would IIoT do?

IIoT would create a pathway to the connected enterprise to get better visibility, boost operational efficiency, increase productivity and reduce the complexity of the process in the industry.

IIoT is introduced to ultimately end the bulging gaps and shortcomings in the manufacturing industry and improve the quality, safety and productivity in a trade.

Optimizing Operations in Manufacturing through IIoT

Let us explore the plan through which manufacturers can shift to smart factories.

IIoT offers optimal practices of devices connectivity and management, synchronization of processes, and advanced analytics to get the best productivity.

Following are the must-to-consider dimensions that manufacturers need to focus on twirling the wheels of the fourth industrial revolution.

Also Read: Cloud-MANET an IoT Collaboration- A New Era of Technology?

Making the equipment Smart and Intelligent:

Currently, the regular working pattern of factories lack proper management because of

  • Different equipment works independently
  • Machineries are fixed or maintained only in breakdown
  • No alternative or proper plan of load balance to schedule maintenance checks

Smart Factories are equipped with intelligent equipment that can self-manage work and integrate with the entire manufacturing ecosystem for the synchronized workflow of processes.

Sensors for Safety:

Installing sensors in manufacturing industry backs in increasing visibility into the functioning of equipment and provides details on possible threshold violations.

Manufacturers can quickly discover existing problems through remote monitoring of computer where sensors are connected to other large networks for in-depth analysis.

IoT just not linger around saving money and time but it prioritizes the safety of workers also.

Sensors installed can also be used to manage and keep surveillance on the workers’ to ensure their safety.

Building a Blended Workforce

Often observed that workers operate on pre-defined schedule regardless of production plans which contribute to wastage of money, efforts and resources.

To optimize the output, it is better to align their work along with machines to develop positive collaboration to deliver outputs as per manufacturing requirements.

Involvement of such result-focused efforts of a blended workforce guarantees to aid in improving the efficiency of manufacturing processes.

Train your employees to adopt the emerging and highly beneficial technologies of wearables and mobile, which helps to instil the concept of enterprise mobility. This eventually helps in improving accessibility and flexibility to undertake tasks.

Addition of latest technology would help in getting access for checking essential data such as work status, work allocation details and instruction in real-time by the entire workforce. It would provide a permit for updating the data as well.

The collaboration of human and machine would resolve the issue of underutilized and unused assets, crossing of deadlines, and management of people as per the urgency of the delivery.

Also Read: How IoT has Influenced The Healthcare Industry?

Predictive maintenance Power:

It is predicted that the entry of the Industrial Internet of Things would redraft the existing operating efficiencies into a positive. It would improve the financial and economic status of the manufacturing industry.

For instance, if a machine does not provide its actual output, then this symbolizes of the fault which could be easily sensed by the connected sensors. The connected sensors would be able to identify the reason behind malfunction and would generate a service request.

Predictive maintenance holds a high power to reduce and stop the upcoming huge losses. It helps manufacturers by predicting which machine might breakdown or enter a dangerous operating condition even before it happens.

The process of condition monitoring is a time-consuming process which mainly involves surveillance of vibrations, sound frequencies and temperature of a given machine to get the information of its reasonable condition.

With the use of sensors, it would become easy to collect and quickly analyze data points, thus making a highly accurate prediction to restrain losses.

The overall equipment effectiveness (OEE) improves with the inclusion of IIOT and sensors. Ultimately effective OEE reduces sudden losses caused to organization by predicting when machines would require maintenance and need services.

By curtailing the machine downtime, manufacturing companies can potentially utilize the machines’ capacity.

Business Process

Manufacturers are aggressively participating in the adoption of the integrated and synced systems that provides better output. The advanced system provides real-time visibility of materials and products throughout the lifecycle, optimize workflow to support precautionary actions for defective products, and optimize plant operations for effective use of resources and assets. Manufacturers are upgrading themselves by dissolving the existing manual management involving tracking people, materials, tasks, and products.

The future companies would be agile, easily adjustable and would cope with the changing demand of the customer without influencing the cost and compromising with the quality.

Conclusion

IIoT would come up as most influencing and promising technology of future which would undoubtedly create an economic change. The prediction and calculation support the conclusion that it would influence the economy of the manufacturing industry positively.

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