Last Updated on August 31, 2023 by Ashish
The objects that we use in our everyday lives are fabricated and put together somewhere by a group of people. Even simple things, such as a pen, have to be manufactured by a company. So, the manufacturing industry plays a crucial role in our lives, even when we don’t realize it. Whether you are a small startup or a large multi-national company in the manufacturing domain, you should definitely start using cloud computing in manufacturing.
Definition: Cloud Computing in Manufacturing
A manufacturing industry is an industry that creates products from raw materials using manual labor, tools, chemical processing, and machinery. It is carried out in a systematic manner with the division of labor. Converting raw materials such as wood, cotton, and livestock into useful products adds value. This increase in the price of the finished product makes the manufacturing industry a very profitable industry.
Before the Industrial Revolution, most products were handmade using human labor and basic tools. After the Industrial Revolution, products started to be mass-produced and the use of machinery and automation increased while allowing for producing larger quantities at lower costs.
Industries in manufacturing must produce products efficiently by:
- Improving and maintaining quality
- Reduce repetitive tasks by automation
- Constantly updating equipment and procedures
- Set realistic goals
- Streamline intake, supply chain, and distribution channels
Types Of Manufacturing Techniques
There are three ways the manufacturing industry can choose to produce and organize its products. These manufacturing techniques are:
- Make to Stock (MTS)
This is a traditional manufacturing technique that is based on forecast demand. The company makes an estimate of how many units might be sold over a period of time. Then, the company plants to produce that amount of products. These goods are often kept in inventory until the distribution of the products.
The company must have enough critical information in advance to make smart decisions on the quantity to manufacture. The advantage of MTS is that the company can plan ahead the raw materials quantity, labor, or equipment needed. The disadvantage is that if the forecast was wrong, the company will be left with surplus inventory and increased overhead.
- Make to Order (MTO)
This technique is the opposite of MTS. For MTO, the company works directly with a customer to understand their needs, product specifications, and quantity. Manufacturing usually only begins after signing a contract.
This technique is most common in manufacturing companies that produce specialized items created for specific purposes. Some examples of these industries are construction, technology, or aerospace.
MTO manufacturers charge higher prices for their products as it is difficult to procure and create. They also carry less inventory than MTS. The disadvantage of MTO is that it does not receive a free flow of demand like MTS so it may face periods where business is slow.
- Make to Assemble (MTA)
Companies get a head start by producing component parts. Then, when a customer places orders, the company starts to assemble the previously manufactured components. This way, the company is already in the process of manufacturing goods and can deliver products faster than MTO processes. However, the company can still face issues of holding inventory if the forecast demand fails.
Challenges In Manufacturing Industry
The manufacturing industry is a vital part of our economy and humanity. Companies in the manufacturing industry have to handle a plethora of challenges while meeting consumer demand and ensuring supply. Below are five common challenges faced by manufacturers.
Forecasting demand allows manufacturers to plan raw materials for future products as well as create products before getting orders from customers. Inaccurate demand forecasting can lead to wasted costs, piled-up inventory, and wasted raw materials. Companies that cannot forecast demand might face overwhelming customer demand that they cannot fulfill, lose customers and decrease sales.
Inventory management is the process of ordering, storing, using, and selling a company’s inventory, starting from raw materials up to finished products. Shortage of inventory can cause supply and demand bottlenecks and cause customer dissatisfaction. Surplus inventory carries spoilage risk, theft, damage, extra overhead cost, and wasted raw materials. Hence, inventory management is very important to a business’s well-being and must be managed efficiently.
Skilled Labor Shortage
Even though many repetitive processes are automated using machines and robots, businesses still require human capabilities to analyze, solve problems, and manage output. The workers from the baby boomer generation are entering retirement so the manufacturing industry is facing a skilled labor shortage.
Fast Technological Advances
The technologies used in factories are changing very quickly and constantly improving. These technologies promise more efficient operations, increased output, and reduced manufacturing costs. There are many types of technologies that manufacturers can implement such as IoT, robotics, automation, and vision, to name a few. To keep up with the fast-paced competitive market, companies must always be ready to replace old technology with new technology.
Supply Chain Disruption
Supply chain disruption is any event that causes disruptions in production, manufacturing, sale, or product distribution. These disruptions can be caused by natural disasters, politics, or pandemics. This challenge leads to goods shortages, price inflation, closing factories, and delayed shipping, and affects a company’s economic well-being.
Intersection of Cloud Computing and the Industrial Internet of Things (IIoT) in Manufacturing
The Industrial Internet of Things (IIoT) stands as a data-centric technology, functioning as a data aggregator that accumulates substantial industrial data necessitating robust storage and processing capabilities. The integration of cloud computing with IIoT serves a dual purpose, encompassing data collection, storage, and the processing of vast amounts of big data. Manufacturing enterprises can strategically employ cloud computing to effectively manage and analyze the extensive data flow originating from their production facilities via IIoT.
By harmonizing IIoT with cloud computing, organizations harness the ability to extract and scrutinize data, furnishing them with pertinent insights to enhance productivity. Cloud computing furnishes IoT devices with a suite of services encompassing computational power, applications, and data repositories. Through cloud computing, contemporary manufacturing endeavors can proficiently exploit data from remote locations, eliminating the necessity for localized hardware or software installations.
In the realm of manufacturing, the integration of IIoT software into smart production setups facilitates the collection of machine-generated data, subsequently stored in cloud repositories for subsequent processing. Cloud computing complements this approach by presenting cloud-based business intelligence solutions that cater to various manufacturing requirements, encompassing machine health monitoring, production oversight, inventory management, and more. The advancement and evolution of IoT and its associated technologies hinge significantly on the availability of cloud services. Consequently, cloud-based IoT solutions play an indispensable role in the transformation of manufacturing industries into intelligent, connected factories.”
Effects Of COVID-19 on The Manufacturing Industry
The COVID-19 pandemic brought the world to a halt for a period of time. Once the economy opened again, initially, it resumed at a slow pace. Below are some negative impacts felt by the manufacturing industry due to COVID-19.
- Delays in delivery – During the early days of COVID-19, most people were not allowed to be physically present at work to stop the spread. However, the manufacturing industry heavily relies on manpower to keep it running. Hence, production came to a stop for a few weeks, sometimes months, which created delays in the whole supply chain. In one survey, more than two-thirds of respondents reported an average delay of three weeks. 15% of them reported a delay of six weeks or more.
- Strained labor market – Before the pandemic, it was already difficult for companies to recruit a new generation of skilled workers. After the pandemic, the labor market strain increased. However, there are new opportunities for companies to upskill current and unemployed workers.
- The increased importance of advanced technology – After the pandemic, companies are more aware of the importance of digital technology in maintaining and monitoring productivity. However, companies are faced with financial constraints which hinder the application of crucial advanced technology.
- Increased financial burden – Not only do companies need to invest in digital technology, but they must also invest in providing additional training in digital technology to their staff. Without proper training, the newly adopted technologies cannot be used to their full potential and may lead to increased loss.
Methods To Overcome Covid-19 Challenges
Below are some management methods to tackle the challenges outlined above.
- Localization and regionalization – MAnufacturers are expecting localization and regionalization of the supply chains to be the new normal in the industry. Localization means locally manufacturing the components or products at its own plant. Regionalization is reorganizing manufacturing into smaller blocks belonging to localized economies. This method can diversify, mitigate risk to business continuity, control transaction cost, and increase supply chain resilience.
- Repurposing – Reconfiguring systems and repurposing materials to support new demands enable manufacturers to continue operations and meet the increasing demand for imported products. For example, car manufacturers repurposed some products to produce respirators that were in high demand during the pandemic surge.
- Digital technologies – Digital technologies are now considered the key to long-term, robust manufacturing. Digitalized supply chains can reduce design complexity, improve communication and connectivity, improve resource flow and redirection, manage existing strategies, and identify more efficient strategies.
- Big-Data Analytics – Big data analytics coupled with predictive engineering are effective in transmitting real-time information to have a constant update on the supply chain which decreases response time when there are issues along the chain. This can minimize capacity loss, improve profit, and reduce downtime.
This is defined as the “use of innovative technologies to create existing products and the creation of new products,”. ( manufacturing.gov).
Types of Advanced Manufacturing
Below are a few examples of advanced manufacturing techniques used to enhance manufacturing processes and systems.
- Additive manufacturing – This technique includes 3D printing, laser printing systems, fused deposition modeling, and other methods that can create complex components from one continuous material, reducing the creation of excess parts. This technique help manufacturers reduce failure points, weight, complexity, and thermal waste energy to name a few.
- Advanced materials – Advanced materials are materials that are precisely mixed to serve a very specific purpose. This method allows for improved material quality and reduces material tradeoff decisions.
- Robotics and automation – Robots have taken over many repetitive tasks in the manufacturing industry such as folding boxes or counting inventory. Industrial robots are hefty and strong to carry out heavy lifting and assembly with precise movement. Using robotics and automation improves a company’s work quality, reduces human error, and improves the overall manufacturing process. Robots are also able to perform tasks that are traditionally hazardous which limits risk, accidents, and waste.
The advanced manufacturing techniques discussed previously provide many benefits to the manufacturing industry. Understanding these benefits will help other companies to embrace advanced manufacturing and improve overall performance.
- Improved quality products – The inclusion of robots and automation reduces the chance of human error. Robots and automation reduce the number of accidents, defects, and overall cost inefficiencies. Workers are now able to upskill themselves and focus on more strategic tasks that involve more intellectual and intuitive work.
- Enhanced productivity – Advanced manufacturing allows manufacturers to scale up or down production processes based on data analytics and market demand. Millions of data can be extracted from machines and robots for analysis. Then, manufacturers can make smarter business decisions based on the analysis.
- Reduced production time – Data from machines allows data analysts to create manufacturing process visualizations through dashboards. These simulations and dashboards help engineers trace problematic processes and design new and improved factory layouts, optimize production sequences, and design ideal output models.
Cloud Computing In The Manufacturing Industry
Other than the aforementioned advanced manufacturing techniques, cloud computing is another technology that can greatly improve manufacturing operations. The current manufacturing environment is fast-paced and constantly changing, and products are customer-driven and short-lived.
Cloud computing can easily fit in this dynamic environment and it performs better than complex, on-premise systems that are costly and cannot adapt to the fast-paced, changing market. Although sophisticated and complex technology was proven to improve productivity, they are simply not agile enough.
Moving applications, processes, and data to the cloud allows companies to focus on activities that are more valuable to the business. Through the cloud, companies can optimize data with sophisticated analytics and virtualize their IT portfolio to encourage innovation.
Benefits Of Cloud Computing
- Lower costs – Outsourcing cloud services can lower the costs of hardware and software because it eliminates the need to build on-premise IT infrastructures which are very costly. Using cloud services also reduces costs in installation, maintenance, and labor. Servers and licenses are provided by cloud service providers by subscription models and paid based on usage.
- Scalability – Manufacturing companies are often met with fluctuating demands. So, with cloud computing, manufacturing companies can benefit from the cloud’s pay-per-use model. When market demand is high, companies can pay more for a bigger cloud scale and when the market demand drops, companies can pay less for the smaller scale used. The cloud is flexible and can be customized based on manufacturing needs.
- Data – All data sent to the cloud are stored and processed over the internet which can then be accessed and analyzed at any time and place. Cloud services, not only store data, but they also provide many cloud-based solutions such as Machine Learning and Big Data analytics providing companies with meaningful information from the data. Some of these insights are consumer demand trends, company supply, and inventory, forecast demand, predicting the onset of faults, redistributing workloads, and more.
- Data Safety – Data stored in the cloud is encrypted and automatically backed up in the case of cyber-attacks and data breaches. Not only that, if a machine is having problems and data cannot be accessed directly at the machine, alternately, the data can be accessed via the cloud which prevents delays in data processing due to machine downtime.
Applications Of Cloud Computing In Manufacturing
- Marketing – Cloud aids in planning, executing, and managing marketing campaigns, marketing customer reach, obtaining insight into the effectiveness of these campaigns, and finding room for improvement.
- Product stock tracking – Companies can match production levels to available stocks, consumer demand, and raw material inventory. Cloud solutions can manage price quotations, order intakes, and customer requests.
- Managing productivity – Cloud can also be used to monitor production levels, trends, and status. Engineers can monitor these changes in real-time to make smarter manufacturing decisions. Machines that are underused can be detected and managed to be used at maximum capacity to avoid wastage and increase throughput.
Google Cloud Platform (GCP)
GCP aims to help manufacturers achieve digital transformation goals using secure, data-driven solutions to reshape development, floor operations, and customer experience.
Below are a few Google GCP Cloud solutions catered to manufacturing industries.
- With Retail Search, retailers can use Google-quality search that is customizable
- Vision Product Search is an ML-powered object recognition and lookup technology that can provide results of similar items from your product catalog
- Relevant recommendations are provided to customers by using AI that understands customer nuances through customer behavior, context, and SKUs.
- Google uses state-of-the-art AI that enables advanced query understanding and produces excellent search results and recommendations.
- Customized recommendations to increase engagement, revenue, or conversions. Companies are able to fine-tune what customers see, filter by product availability, diversify product displays, and more.
- Quick start-up – Companies can quickly connect data with existing tools such as google analytics 360 or BigQuery as well as integrate data, manage models, and monitor performance from an intuitive GUI.
Visual Inspection AI
- Run on-premises. Deploy these high-performance inspection models anywhere in the factory.
- Deliver significant ROI by reducing inspecting costs, rework, and scrap, and improving key quality metrics.
- Use their superior AI technology to tackle the most challenging inspection tasks.
- Assembly inspection and detection of even the most subtle defects at various stages of the assembly process.
- Locate even the tiniest and most complex defects on any surface type.
- Scale on-premise
- Quick start capability – start by using models with few labeled images because active learning will automatically suggest additional images for the operator to label and further improve model performance.
Amazon Web Services helps manufacturers transform operations using advanced cloud solutions which include machine learning, IoT, robotics, and analytics. AWS solutions allow you to focus on optimizing production, creating new smart products, and improving overall operational efficiency across the supply chain without worrying about the infrastructure.
Below are a few Amazon Web Service solutions catered to manufacturing industries.
- Offers the broadest and deepest computing platform
- Has 500 instances and a choice of the latest processor, storage, networking, operating system, and model of your choice
- The only cloud with on-demand EC2 Mac instances.
- Delivers secure, reliable, high-performance, and cost-effective compute infrastructure for enterprise applications
- Can access the on-demand infrastructure and capacity you need to run HPC applications faster
- Scale capacity within minutes with SLA commitment of 99.99% availability.
- Provides secure computing with security built-in into the solution with AWS Nitro System
- Highly scalable cloud storage that stores object data within buckets.
- Store any amount of data for a range of use cases such as data lakes, websites, backups, archives, and analytics.
- Designed for 11 9’s of durability
- Build a data lake on this service to run big data analytics, AI, and Machine Learning to unlock insights.
- Meet recovery time objectives, recovery point objectives, and compliance requirements
- Archive data at the lowest cost
- Build fast and powerful web-based cloud-native apps that can scale in a highly available configuration.
Azure recommends its data-centric approaches to meet the challenges faced in manufacturing. With Azure, companies can obtain personalized experiences, gain visibility across the supply chain, and build innovative business models with secure and scalable cloud technology.
Below are a few Azure solutions catered to manufacturing industries.
Azure Synapse Analytics
- Limitless scale for insight delivery from all your data, across different data warehouses at blazing speed
- Expand insights from all your data through powerful machine-learning models
- Significantly reduce project development time with a unified experience
- Eliminate data barriers and perform data analytics on business and operational apps data
- Unified analytics platform for data integration, exploration, warehousing, analytics, and machine learning from a single, unified environment.
- Supports both data lake and warehouse use cases with optional cost-effective prices
- Build critical data warehouse on proven foundations using top SQL engine
- Build a code-free visual environment to easily digest data from more than 95 native connectors
- Build frameworks, tools, and capabilities for developers and data scientists of any skill level and on your terms
- Deploy mission-critical AI solutions
- Apply AI in manufacturing responsibly.
- Modernize business processes with task-specific AI
- Accelerate development using business logic that enables solution launch in lesser time
- Azure cognitive service is available for comprehensive and customizable APIs for vision, speech, language, and decision-making.
- Develop with your choice of tools when creating and deploying models
- Create and deploy models at scale using automated and reproducible workflows.
OCI Oracle’s Cloud services help companies streamline global, mixed-mode manufacturing to make anything, anywhere, with intelligent, optimized, and integrated solutions powered by IoT and AI.
Below are a few Oracle solutions catered to manufacturing industries.
Oracle Product Lifecycle Management
- Unify processes on a single data model for faster decision-making
- Build smarter innovation pipelines
- Design, develop, and manage new product introductions and changes more efficiently
- Leverage single enterprise product record to provide the resilience needed to support complex business transformations
- Drive closed-loop quality management for real-time transparency and traceability
- Innovation management – faster innovations, ideate everywhere, manage requirements and concepts.
- Product development – Minimize design cost, rapidly develop and launch, reduce supply risk, and accelerate change management
- Product master data management – Item mastering, integrated collaboration, ERP migration, and consolidation
- Asset management – Full lifecycle support, gain insight into an asset, streamline processing, and drive end-to-end processes
- Smart machine integration – Track assets, connect assets to IoT, monitor assets, drive predictive maintenance
- Maintenance planning – Integrated process, forecast, and auto schedule preventive maintenance, plan work orders with skilled technicians
- Optimize maintenance scheduling with AI
- Reach higher efficiency levels with predictive maintenance
- Increase uptime while reducing maintenance costs
It suggests intelligent operations and hybrid cloud infrastructures create sustainable and profitable manufacturing operations.
Below are a few IBM solutions catered to manufacturing industries.
- Provide AI and IoT-driven solutions management, production optimization, and visual inspection for quality assurance challenges
- Reduce downtime
- Improve maintenance practices and plans
- Understand assets in the operational context
- IBM Maximo Application Suite: Integrate with business management systems to improve operations, reliability, and performance
- IBM Maximo APM: Monitor, maintain, and replace assets
- IBM Maximo Visual Inspection: Monitor production and diagnose issues
IBM Enterprise asset management software and solutions
- Gain greater control of complex environments
- Streamline and unify operations across silos
- Boost operational resilience and reliability
- Artificial intelligent solutions
- Maximo Application Suite EAM
- IoT for workplace safety
- Asset optimization services
This Cloud can digitalize industrial practices using edge computing and data intelligence.
Below are a few Alibaba Cloud solutions catered to manufacturing industries.
- Secure data communication
- Supports multiple data sources
- Efficient R&D
- Visualized data analysis
- Easy and convenient data management
- Visualized management of metadata
- Data security
- Change stability
- Efficient R&D
Machine Learning Platform for AI
- Visualized interface
- End-to-end solution
- Myriad algorithms
- Powerful computing capability
- Data mining and analysis
- Natural language processing
Cloud Case Studies
Google Cloud – LG Corporation
LG Corporation headquartered in Seoul, South Korea had revenues of 62.3 trillion KRW in 2019. LG CNS is a subsidiary of LG Corporation that provides IT services. One part of LG CNS wanted to improve model accuracy for glass substrate used for manufacturing LCD TV panels. Inspections were labor-intensive and time-consuming.
LG worked alongside Google Cloud to develop a Visual Inspection AI solution to automate manufacturing quality processes. The AI detects defects in LCD screens to automotive fabrics on the assembly lines.
LG leveraged Google Cloud edge offerings to run models for defect detection with minimal latency and at scale to overcome bandwidth constraints. With Google Cloud, LG can automatically train ML models with minimal manual image-labeling efforts. LG was able to inspect 200 mages in 0.8 seconds.
With Google Cloud, LG was able to save $20 million per year, automated defect detection with 99.9% accuracy, and increased throughput.
AWS – Weir Minerals
Weir Minerals is a global market leader in supplying engineered solutions in the mining industry. Their customers require fast order fulfillment lead times. To do this, they need to be able to effectively track and manage complex customer order flow.
Using 42Q’s SaaS solution, Weir Minerals created a blueprint for digitizing shop floor operations so that operators can quickly roll out and modify the environments. Previously, they used on-premise solutions which used massive capital expenditure and process overhaul to implement. Hence, the company opted for a cloud-based solution, the 42Q hosted on AWS.
They chose AWS because it provided the security, support, and assurance needed to deliver the experience. Resultantly, the company was able to reduce lead time by 30%, increase on-time delivery by 10%, and 30% increase in throughput at bottleneck operations.
Kennametal is a company that delivers industrial parts to global customers in many industries. The company migrated IT resources to Microsoft Azure as it recognized the importance of data in business. Microsoft Power BI was also used to uncover insights from data.
Previously, the plant used a lot of manual processes from tracking orders to diagnosing machines. Thanks to investments in Azure, Power BI, and Azure IoT Hub, the company now manufactures at a more efficient level.
As Kennametal proceeded with modernizing manufacturing through data-driven decisions, it realized that on-premise infrastructure could not accommodate the large amounts of data produced by a modern factory.
Data and IoT efforts improved machine setup times by almost 50% and increased press availability by 50%.
The Precision Group U.A.E manufactures aluminum extrusion dies, tools, press tools, blow molds, precision molded plastic products, and thermo-formed industrial packaging. The company ran on a legacy system for more than 25 years which was inefficient. They were not able to manage to report and lacked an integrated system. Visibility was also low on the shop floor.
To address these challenges, they needed to modernize their systems. Hence, they found Oracle offered the best in the cloud, in terms of breadth of applications, seamless integration, and use of advanced technologies in the solutions. Between Oracle and SAP, the company chose Oracle as it was proven to be a leader in the cloud, mature, flexible, agile, and provided more innovative features. Oracle Cloud solutions were embedded into one package which is more efficient and easier to use.
Using Oracle, they were able to achieve increased efficiency and end-to-end visibility. Precision now has complete visibility using advanced analytics, dashboards, increased collaboration, and faster decision-making.
Manufacturing companies must stay ahead of the competitive market with modernized and smart factory systems. One established technology that can elevate a company’s manufacturing system is the cloud. Companies can use the cloud to securely store billions of data extracted from machines in a cloud database. Additionally, cloud service providers also have many cloud-based ML, AI, and IoT solutions that companies can use on a pay-per-use basis to extract crucial insights into the whole manufacturing system and line. The case studies discussed above are proof that cloud-based solutions are the way to go if manufacturers want to operate in the most efficient and cost-effective way.