5 Smart Manufacturing Trends for 2019
Smart manufacturing is a conglomeration of disruptive technologies that enable easy connectivity and automation across all processes involved in the industry’s ecosystem. As manufacturers across the globe are slowly transitioning, we thought it would be the right time to see what’s trending, and how the technologies will make an impact on growth, operations, and revenue.
How Disruptive Technologies are bringing in Digital Transformation in the Supply Chain Process
The supply chain process has undergone a major digital transformation in recent years. New age disruptive and emerging technologies have helped create cost-effective and highly efficient processes, that have brought about rapid growth for this segment. The industry is seeing great strides in the area of predictive modeling, which is enabling businesses to cater to new and growing demand efficiently. Supply chain businesses everywhere are in a transition phase, integrating their legacy processes with emerging technologies. Here’s a look at some of the popular supply chain digital transformation technologies that are most sought after. Lights-out Planning This technology works on the concept of “segmentation and synchronization” of all the activities involved in the supply chain process. Implementing lights-out planning can result in significant improvement in productivity and efficiency, and a reduction in working capital. It replaces human input for the planning process with machine learning which greatly aids in forecasting. From real-time scheduling of shop floor communication to the final rollout of the product, lights-out planning can offer seamless automation of the supply chain process. Blockchain Solutions Blockchain is a tamper-proof digital ledger that enables manufacturers to keep track of the purchase volume, irrespective of who initiated it – the employees, partners, or subcontractors. This technology eliminates the need to recruit a professional team to audit transactions and the price-verification process. Manufacturing companies also benefit from the fast closure of digital contracts and payments. Blockchain is also a great technology to secure supply chain transactions and identify malpractices instantly. 3D printing 3D printing was first deployed in the prototyping division of the manufacturing house. In today’s fast-paced market scenario, 3D printing has enabled supply chain processes to run perfectly even for a batch size of only one. Product designs can be customized by the customers on the fly, while engineers can design spare parts in a short time. The high-level business value of this technology is the agility with which product customization can be carried out seamlessly and effortlessly. Reduction in manufacturing, production, and distribution time is the single largest benefit here, while the process also generates minimal to no waste, reducing the carbon footprint of the manufacturing house. Artificial Intelligence (AI) & Deep Learning Amongst the new disruptive technologies, Artificial Intelligence has the greatest potential to transform the supply chain process. From building prototypes to automation, and real-time decision-making, AI technology can be applied to every aspect of the supply chain. The technology enables manufacturers to gather real-time buying behavior to better understand customer needs. AI empowers manufacturers to gain predictive insights on how to improve operations and improve customer engagement with Natural Language capable applications for voice and text. The above disruptive technologies have changed the supply chain process from a cost overhead to a revenue-generating one. Manufacturers across the globe are actively adopting these technologies to suit their production and market needs. The key to implementing these technologies is finding the right partner, with the necessary experience in the required field of automation. This adds to the overall efficiency of implementing technology and driving bottom-line growth. Are you looking to streamline your supply chain processes for greater operational efficiency? InApp is an experienced technology partner helping companies implement cutting-edge disruptive solutions and we would be glad to help. Contact us to learn more.
Industrial Internet of Things: IIoT Benefits & Challenges
The Industrial Internet of Things (IIoT) is the single biggest technical innovation in recent times. It has slowly gained inroads into our lifestyle, making devices smarter, and communications faster. IIoT enables easy collection and communication of data, which helps companies to make informed decisions. Benefits of the Industrial Internet of Things IIoT offers a huge spectrum of business functionalities by enabling the integration of multiple datasets. Mobile phones harness the benefits of IIoT in the best possible manner. Accessing IIoT solutions via mobile applications makes them more accessible, making it easy to transmit data. For example, some medical devices with in-built sensors can help obtain health information from the patient, and transfer it to a mobile app for further analysis. IIoT-based farming employs sensors to remotely monitor weather and environment conditions, farm statistics, and livestock. IIoT offers a wide range of offerings for the retail industry, including Wi-Fi tracking systems, predictive maintenance, tracking transport systems, warehousing, and smart stores. Manufacturers can monitor truck mileage and engine health, while effectively optimizing truck routes. For large-scale manufacturers in the airlines and car business, IIoT enables ground technicians to get alerts for maintenance schedules and daily production. Despite its multiple benefits, implementation is still a challenge in many ways. Challenges of the Industrial Internet of Things While it is very clear that IIoT technology adoption can sprint the company’s growth many times over, its implementation requires a fairly large financial investment for setting up dedicated IT teams and infrastructure. For IIoT to be a success, the following needs to be executed. Shop floor operators have to monitor assets in real time and ensure that the machines perform optimally. This requires setting up the necessary IT infrastructure to get better visibility of machine performances. Management needs to ensure that all disparate systems are bound through IT, in order to ensure data security and faster access to real-time intelligence. Knowledge transition from the aging workforce to new teams needs to be conducted so that new digital technologies contain all the necessary know-how for operations. Setting up storage and communication technologies to leverage real-time data. This is also important to ensure data does not get siloed, which may lead to technical challenges. Ensure a robust security system is in place to protect organizational and financial data from cyber-attacks. It also includes coming up with a suitable mitigation plan to overcome risks. IIoT challenges for manufacturers are all about cost and implementation. By overcoming the above-mentioned steps with suitable technology solutions, companies can enjoy the benefits of improved productivity and growth. Do you want to harness the power of IIoT for your organization? With 21+ years of experience, InApp leverages disruptive technology solutions that can help you make intelligent data-driven decisions. To learn how to accelerate growth, while minimizing costs, contact us.
Blockchain Solutions by InApp
Through its blockchain solutions, InApp has been bridging the gap between the said technology and finding its usage in different modern applications. Learn here how we’ve been doing it.
Driving Digital Transformation in the Manufacturing Sector with Artificial Intelligence and ML
Cutting-edge, disruptive technologies like Artificial Intelligence (AI) and Machine Learning (ML) are driving process automation changes that provide corporates with unparalleled abilities to make faster decisions and drive timely outcomes and deliveries. Manufacturing is a segment that has been slow to change because of its long association with legacy systems and complex processes. What the industry did not expect is that disruptive changes are transforming all layers of the industry. Manufacturers are facing challenges to improve product quality, minimize downtime, meet highly variable demand, and cater to personalized products that require high automation efficiency. AI and ML are playing a big role in helping manufacturers transform to achieve these goals. From supply chain management to predictive maintenance, manufacturers need technology-driven innovations that can integrate processes and drive seamless operations. Coupled with the need to improve employee efficiency and drive R&D efficiency, the manufacturing industry faces multiple challenges to meet the growing demands of its customers. Building Business Value with AI and ML Bringing AI and ML technologies into the manufacturing sector can be a dream situation, given that the benefits range widely from improving operational efficiency to driving bottom-line growth. Let’s take a look at how each of the below parameters is influenced by AI and ML technologies. 1. Sensitizing Predictive Maintenance According to a PwC report, ML analytics can improve predictive maintenance processes by 38% in the next five years. Through improved process visualization and automation, the algorithms can help manufacturers expect a steep rise in their growth rate. By reducing supply chain forecasting errors, companies can achieve better product availability, and more efficient transport and warehousing administration. 2. Raising the Cost-Benefit Value Integrating AI and ML algorithms into procurement data can aid in strategic sourcing and cost management. Machine Learning-based root-cause analysis can bring down annual predictive maintenance costs, while AI-powered predictive maintenance ensures seamless operations and high yields. AI-based optimization can reduce machine downtime and inspection costs. This improved accuracy causes a ripple effect, sometimes contributing to up to a 50% reduction in manufacturing costs. 3. Asset Management and Inventory Optimization Adopting AI and ML can drastically increase your asset tracking accuracy and inventory monitoring, across global locations, thus enabling shop floor teams to gain increased visibility into their supply chain movement. Inventory optimization through ML algorithms can enable marketers to manage their demand supply, taking into account time-to-market variables. Real-time monitoring of shop floor operations offers the necessary insights to achieve optimal production schedule performance and higher visible control of maintenance activities. 4. Leveraging Real-time Testing Intelligence One of the major roadblocks in manufacturing is the testing stage. Achieving accurate prediction of calibration and test results using machine learning algorithms enables easy isolation of bottlenecks, and streamlining of the end-to-end test processes. AI and ML can certainly enable manufacturing companies to go past the boundaries of traditional tools and processes, to procure real-time intelligence that can drive real-time accelerated growth. 5. Raising the Operational Efficiency Bar Embracing AI and ML leads to a reduction in downtime due to human errors and ensures streamlining and linking of all in-house and subcontract processes. This results in the company gaining more time for innovation and R&D to cater to new market segments. A powerful operational advantage is that AI and ML-based predictive maintenance brings factory downtime to almost zero for greater efficiency. Embracing AI and ML Disruptive technologies such as AI and MI have a positive impact on manufacturing processes, delivering multiple benefits to drive business growth. InApp provides smart digitalization strategies setting the stage for long-term growth and market leadership. InApp solutions offer automation benefits, NLP capabilities, object recognition features, and real-time predictive insights. We help you choose the right AI solution that can drive digital transformation at a fast pace, and one that suits your current business needs. Interested in exploring a transformative digital solution with us? With over 21+ years of experience in the manufacturing sector, we would be happy to help. Click here to get in touch with us.
3 Major Challenges Associated with Blockchain Solutions
Many companies are using Blockchain technology for the finance trade, healthcare, cloud storage, and cybersecurity. InApp is contributing its own with our blockchain solutions. Learn what are the three major challenges being faced by Blockchain Technology.
Text Analysis and ElasticSearch NLP
Natural Language Processing (NLP) has evolved greatly over recent years and it’s being widely used to understand and analyze human communication. Combined with Deep Learning, technology can categorize a user’s interest based on their language. For instance, when a foreign user updates a post in their native language, Facebook presents it with a “Translate” option for non-native speakers. Another great example of NLP in action is the voice assistants such as Alexa and Google Home. They have the ability to create a voice profile of the owner and can tell the difference between them and any newcomers. NLP helps these devices in identifying the language, slang, and sentence formation of each individual to differentiate between users. NLP is not just limited to voice assistants; it has several exciting potentials in multiple areas. used in more areas of interest than just as a voice assistant. Companies such as Airbnb and Uber use NLP in their search engine to enrich the user experience and narrow down the search results. ElasticSearch and Apache Solr are some of the most advanced search engines that make use of NLP by performing deep analysis of key phrases to understand the query better. For example, when the search engine encounters the word “ASCII”, NLP helps in identifying it as an Acronym which in turn optimizes the search results by arranging the desired information first.
Disruptive Technology in Manufacturing: Transforming the Industry
Disruptive technology is driving massive changes in multiple verticals across the world, from finance to healthcare. Surprisingly, manufacturing has only recently harnessed the latest digital innovations for greater efficiency, opportunities, and revenue. Digitization is no longer an option, manufacturers who are looking to stay ahead of the game must embrace digital transformation in the era of Industry 4.0. Disruptive technologies such as Artificial Intelligence (AI), Machine Learning (ML), Industrial Internet of Things (IIoT), Augmented Reality and Virtual Reality, Big Data, wearables, and 3D printing are reshaping the manufacturing industry as we know it. Research by PwC indicates that a whopping 86% out of 2000 manufacturers are looking forward to costing reductions and greater revenue due to digital transformation efforts during the course of the next five years. Disruptive Technology in Manufacturing – Let’s take a look at some of the changes taking place in the industry: Optimization of the Supply Chain Manufacturers often struggle with a lack of precise knowledge of the various stages of the supply chain. This is all set to change with the advent of the Industrial Internet of Things (IIoT) and more sensors at every stage. In addition, AI and ML predictions will help optimize inventory. The power of automation and IIoT-enabled tracking will see drastic increases in efficiency. Cloud computing can provide a single window of transparency across the entire supply chain. Autonomous vehicles could also optimize the supply chain with more efficient deliveries and clear tracking across vehicles. Zero Downtime with Predictive Maintenance Downtime is one of the biggest losses for any manufacturer. Predictive maintenance is the key to cutting downtime to almost zero. This adds up to massive cost and time savings, which ultimately leads to greater profitability. This predictive capability will be powered by AI and ML in tandem with cloud computing and the Industrial Internet of Things (IIoT). This technology will enable precise predictions at both component and system levels for advanced maintenance. This predictive power will lead to massive improvements in efficiency and productivity, with the elimination of wastage due to equipment downtime. Greater Employee Efficiency It’s a brave new world with digital disruption and Augmented Reality (AR) and Virtual Reality (VR) at the new frontier for training employees via immersive programs. It is much easier to teach the workings of machinery and equipment in a visual manner that is easily understood. AR allows an instruction-filled map to be cast on complex machines. Skills become almost downloadable with this technology. Besides training, AR can also help an employee do their jobs better when an overlay of simulated information supports the task they are completing. AR technology also allows tasks such as field testing to be executed remotely. Wearables and exoskeletons in tandem with AR and VR are improving training, productivity, and employee efficiency for industrial workers. Improved R&D and Testing Efficiency Organizations spend billions in the R&D and Testing stages of Manufacturing. Disruptive technologies such as AI, ML, and AR are proving to be game-changers in this space. With the power of AI and ML, it is possible to rapidly simulate many options in a realistic manner which is extremely efficient for both these stages. The capabilities of Augmented Reality (AR) and Virtual Reality (VR) drastically improve the ability to test a product in varying conditions. This leads to greater efficiency for both these stages along with cost savings. Manufacturers predict that manufacturing efficiency will grow annually at 7 times the rate of growth seen in the decade of the 1990s. It is an exciting time for manufacturing with automation and disruption reshaping all layers of the industry. If you are interested in exploring a transformative digital solution for your organization, please feel free to contact us. InApp is passionate about empowering clients, and with over 21+ years of experience in the manufacturing sector, we would be happy to help.
3 Business Benefits from Text Mining using Natural Language Processing (NLP)
In the recent era of digital technologies, Text is the most popular means of communication between a given set of individuals. Whether it is a social media post, an email, or a text message, it has always been easier to express our thoughts in the form of texts. By accumulating billions and billions of data, there arose a possibility to harness that text-based information and analyze it for different business benefits.
A DevOps way of Managing IT Infrastructure
Be it a startup or an enterprise, managing the IT Infrastructure becomes tedious as the business starts to grow. DevOps introduces specific best practices into the organization to make Infrastructure Management a more straightforward task.