Manufacturing industries are required to meet ever increasing demands for quicker delivery and increased production. To help manufacturers meet these needs Cloud technology can be introduced into more and more areas. The benefit from Cloud enabled technology is that the company can stay “open for business” outside of strict business hours, stay more securely connected with their customers, their extended and often global supply chains, and all levels of the manufacturing industry.

It is estimated that around the world, 90% of companies are using some type of Cloud technology. So, in order to stay ahead of the competition, manufacturing industries must adapt and change to survive. It is estimated that by 2023, almost half of all software used by manufacturers will be cloud-based. 

What Is Cloud Computing and How Does It Benefit Manufacturing?

Cloud computing uses the internet to store information on secure servers and this technology has an increasing use in manufacturing operations and production processes. Compared to traditional technology that adopts computers which have to have constant software updates, cloud computing offers several advantages, such as:

• Reliability: fewer technical problems using Cloud-based technology instead of individually updated computers
• Cost saving: No need for costly in-house servers
• Scalability: grows with the business and can be easily scaled back when required
• Updates: Technology stays updated. IT departments don’t waste time installing the latest software
• PEU: Better productivity, efficiency and utilisation goes up whilst down time goes down
• Communication: Instant communication across a business gives companies a competitive edge
• Centralised management: Access via any computer in the organisation, improving management capabilities.

This type of Smart manufacturing is a new breed of technologies, which allow computers and devices to communicate with each other to optimise productivity and efficiency. Even smaller businesses that don’t have a huge IT infrastructure or budget to implement smart manufacturing can afford and implement Cloud technology. 

Applications of Cloud Computing in Manufacturing

In manufacturing, cloud computing offers numerous solutions for every part of the process, from marketing to productivity. Integrating cloud technology into multiple operational areas increases the benefits gained from using it. A few common applications of cloud computing in the manufacturing sector include the following:

Product Development

Product planning and development tie heavily into production. By combining product planning and development information into supply chain data and communications, manufacturers can prepare their operations for full production. With comprehensive integration, products can move from idea to engineering to prototype to small production and finally to full-scale manufacturing and shipping much faster.

Production and Stock Tracking

Once production starts, cloud technology can benefit the process of producing and stocking products. Combined with a good enterprise resource planning (ERP) system such as Microsoft Dynamics D365F&O, companies can match their production levels to available stock and sales. The ERP can manage price quotes, order intake and customer requests. Fewer mistakes happen when using a standard product to track these, thus lowering order cycle times.

Productivity Management

Manufacturers do not produce the same level of products throughout the year. To meet changing needs, manufacturers can use cloud-based applications to monitor when to change production. Plus, continuous communications through the supply chain ensures manufacturers have raw materials on hand to amend orders to meet the ever changing needs of production.

SaaS Solutions in Cloud Technology in Manufacturing

Cloud technology has three main forms:

• SaaS: software as a service offers internet-based programs for use by anyone in a company. Among these, SaaS ranks as one of the simplest solutions to quickly integrate into a business.
• PaaS: platform as a service which companies use to develop their own applications in rented production or development solutions.
• IaaS: infrastructure as a service. IaaS lets manufacturers of all sizes use an enterprise-level infrastructure to help with operation scaling, data storage and information processing. 

SaaS is used in the manufacturing industry. SaaS manufacturing software benefits include:

• No need to maintain servers
• No need to update locally stored software
• No loss of data from computers or hard drives
• All files stored centrally and securely

By integrating SaaS businesses can enjoy several advantages:

• Real Time Data Capture
• Single source of the truth
• Future scalability
• Improved Collaboration
• Same files in the same place using the same solution

Cloud Computing in Manufacturing Automation

Manufacturing Automation is the use of equipment to automate systems or production processes. The end goal is to drive greater efficiency by either increasing production capacity or reducing costs, often both. 

Automation has become known more as using machines to reduce work performed by humans. It has become associated with electromechanical systems that are programmed to perform many types of processes. While automation may not be right for every manufacturer, most companies are able to find benefits in automation. With the adoption of Cloud Computing, Manufacturing Automation technology can now communicate Real Time to upload data directly from sensors housed in an array of manufacturing and supply chain situations to an ERP system. Benefitting the business in areas such as:

• Reducing downtime
• Provide predictable maintenance
• Improve decision making

Allowing businesses to effectively control, manage and report in Real Time throughout the Manufacturing and Supply Chain processes. The following are just some of the technologies which can easily integrate:

• Dynamic Dimensioning: Capture dimensions of goods running on an automated conveyor line for revenue recovery and data transparency. 
• Dynamic Weighing: High-speed dynamic weighing of parcels and items moving on a conveyor. Simply integrated with barcode readers and cameras for advanced parcel data capture. 
• Pallet Dimensioning: Accurately measure the volume of pallets and non-conveyable items for dimensional weight pricing and are easily integrated with scales, barcode readers and cameras for a complete freight data profile.
• Static Dimensioning: Static dimensioning ensures accurate measurements in manual or semi- automatic operations and is typically provided with a table-top scale and barcode reader. 
• Scale Integration: Perfect for offices, mailrooms, shipping departments and retail parcel stores, postal scales connect seamlessly to PC-based carrier manifesting or shipping software to capture accurate weight data
• Weigh Modules and Load Cells: Precision weigh modules enable accurate weighing. They facilitate mechanical integration into machines or systems and protect the load cell. Unique features assure safe installation. Simple load cells are available for direct integration into machines. Dedicated accessories enable proper load introduction to ensure accuracy.
• Floor Scales: Ensure efficient operation with the right floor or pit scale. Easily customised with ramps and lifts. Scales can include weight range, available space and work environment
• Forklift Scales: Heavy duty scales designed to endure the knocks of industrial use. Forklift scales record accurate weight simply by lifting the pallet, eliminating need to move the pallet to a scale.
• Data Management Software: Powerful data management software is designed to give you the most from your weighing, identification and dimensioning equipment

Cloud Computing Incorporating Sensors In Manufacturing

Sensor technology plays a variety of essential roles in machine automation. Sensors provide information about products during manufacturing. They deliver updates about the condition of the equipment, to help guide maintenance and prevent downtime. Sensors also provide feedback on the motion of the motor to ensure accurate positioning. Sensors can be used to determine properties of objects such as position, distance, and proximity. Sensors also can be used to evaluate characteristics like temperature and colour. With the introduction of Cloud Computing, Sensor technology can now communicate Real Time to upload data directly to an ERP from sensors housed in an array of manufacturing and supply chain situations, such as:

• Presence/Absence Sensors – Presence/absence sensors use non-contact technology to detect the presence or absence of the object of interest and report the results to the controller or drive using an electrical signal. Because these sensors are noncontact, they minimize damage or wear to the device under test and to the sensor itself.

The environmental conditions of the application drive the specific technology choice. Key factors to consider include temperature, ambient light, moisture, airborne particulates, shock and vibration, and other contaminants. In addition, some sensor technologies require a metal target in order to operate. 

• Distance Measurement – Time-of-flight measurements can be used to detect the distance to an object of interest or its position. Initially, optical time-of-flight measurements required laser-based sensors. More recently, manufacturers have developed LED-based systems that detect and process diffuse backscatter to return distance and position information. Time-of-flight measurements can also be taken using ultrasonic sensors.
• Colour Sensors – In many products, colour is just as important as function. Colour sensors provide quantitative method for analysing colour in everything from labels to textiles to paints. Colour sensors analyse the spectral content of the light reflected from a surface, comparing it to an internal reference to obtain a result. The colour of light used for illumination is particularly important in these applications since the reflection spectrum is only a subset of the incident light.
• Condition-Monitoring Sensors – Modern manufacturing puts the emphasis on maximizing operational equipment effectiveness (OEE) and increasing uptime. Condition monitoring is an essential tool for achieving this goal. Condition data provides insight into the health, operation, and performance of equipment, facilities, and even the products being manufactured. This typically encompasses factors like temperature, pressure, humidity, vibration, and current or voltage.
• Data Sensors – Some applications require information to be transferred about the products being manufactured. On an automobile assembly line, for example, data sensors can be used to read out the specifications of the order so that the chassis coming down the line gets the right options and the right colour of upholstery. Data sensors can also present information about assets for tracking or maintenance purposes. Data sensor types include barcodes, QR codes, and RFID tags. 
• Mark Sensors – Mark sensors are specialty sensors designed to detect the registration marks put on materials typically to guide operations like printing and packaging. Also known as contrast sensors or eye sensors, the systems are distinct from standard machine-vision systems used in automation. These sensors evaluate the field of view based on contrast rather than on colour or pattern. The system converts the image to grayscale. It then compares each region in the field of view to some set switching threshold. 
• Photoelectric Sensor – Photoelectric sensors, or optical sensors, leverage the changes to an optical beam caused by interaction with the object under test. A photoelectric sensor consists of an emitter that generates the optical signal and a receiver (typically a photodiode) that detects it. Photoelectric sensors can be classified as through-beam or reflective; reflective photoelectric sensors can be further broken down into diffuse and retroreflective types.
• Through Beam Sensor – In through-beam sensors, the emitter and receiver are placed on opposite sides of the objects of interest. The beam either passes through to the detector or is blocked. This type of configuration is good for detecting the presence or absence of components, or checking their position. 
• Fibre – Fibre sensors are optical sensors packaged in a rugged, economical, easy-to-deploy solution. As with conventional photoelectric sensors, they involve emitter and a detector. Unlike conventional systems, they do not use free-space optics. Instead, the light is confined to an optical fibre both for transmission from source to object and return of the captured signal to the detector. Fibre sensors are particularly useful in harsh environments, for example with high temperatures or contamination. 
• Capacitive – Capacitive sensors monitor the change in capacitance between the sensor plate and the object of interest. Capacitance varies as a function of the size and distance of the sensing object. These sensors are simple and solid-state. They can be used for metallic objects, resins, liquids, and powders. On the downside, they are strongly affected by factors like temperature, offset, surrounding objects, and EMI from power and signal cables.
• Inductive – Inductive sensors are based on the principle that eddy currents can change the impedance of a conductive material. The sensor applies an external magnetic field to induce eddy currents in the object of interest. A detector coil in the sensor generates an AC magnetic field for readout.
• Eddy-current sensors – these can only be used with metallic objects. Various types of eddy-current sensors exist, including versions designed for use with aluminium. Inductive sensors are noncontact. They are extremely robust and generally impervious to contamination like oil and dust. 
• Magnetic – A magnetic proximity sensor consists of a reed switch that is controlled by a magnet. When a magnet mounted on the object under test nears the reed switch, the switch closes. Magnetic proximity sensors are EMI immune. They also are not affected by contamination like oil and dust.
• RFID – RFID sensor systems pass data from tagged objects to RFID readers. An RFID system consists of two parts: the RFID tag and the RFID reader or interrogator. Tags may be read only, write once read many, or read/write. Tags are classified as active, passive, or passive with battery assist. A passive tag needs to be interrogated by the RF signal from an active readout device. The readout device must be in proximity to the tag for a successful read.

Ultrasonic – An ultrasonic sensor uses ultrasonic waves to calculate the distance to an object or to register its presence. Ultrasonic sensors can operate in transmission or reflectance mode. Transmission sensors, or through-beam sensors, consist of the detector on one side of the object under test and a receiver on the other side. The output signal is either blocked or attenuated by the objects.