- April 3, 2019
- Posted by: InApp
- Category: Artificial Intelligence, Blockchain, Cloud Computing, Manufacturing
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.
1. AI and ML will sensitize predictive maintenance
Artificial Intelligence (AI) and Machine Learning (ML) algorithms, when used in tandem with Industrial Internet of Things (IIoT), can be leveraged to forecast errors, plan for timely resource availability, and monitor warehouse administration. This enables predictive maintenance which tackles issues ahead of time resulting in almost zero downtime. Leveraging AI and ML algorithms for root-cause analysis allows precise predictions at both component and system levels for advance maintenance, and lowering of annual predictive maintenance costs.
2. Collaborative robots will enable up-skilling of employees
Amongst the new wave of disruptive technologies to hit the manufacturing industry, collaborative robots are most sought after because they help improve operational efficiency right from the shop-floor level. They serve the purpose of integration and control, through the use of advanced sensor systems and cameras. Robots find use in the fitting and assembly lines where they are made to operate 24×7 for continuous production output. They help augment the capabilities of the workforce by relieving them of monotony, and cutting down worker costs where non-value-added activities are involved, freeing employee time for up-skilling activities.
3. Robotics-as-a-service (RaaS) will lower the barrier for SMBs to invest
RaaS allows manufacturing companies to use robots for a subscription fee, thereby eliminating the overhead of purchasing costs. This makes RaaS a profitable proposition for both small and medium businesses. A large part of the capital amount saved from investing in RaaS can be leveraged in areas such as R&D and new acquisitions. RaaS allows robots to be connected over the Internet and have instant access to cloud storage. With seamless data processing and efficient workflows, manufacturing companies can expect to produce on time, without any delay in the supply chain.
4. Cloud robotics & APIs will bring customization to the forefront
A MarketsandMarkets report states that “Cloud Robotics Market will be worth 7.51 Billion USD by 2022”. This is mainly due to the recent development of robotic platforms that have attracted small and medium businesses around the world. Moreover, new APIs are enabling manufacturers to fine-tune robotics solutions to suit their customer and market demands. By bringing together complementary technologies like cloud robots and APIs, manufacturing as an industry segment is set to gain big time in terms of innovation and growth.
5. 5G & Multi-access Edge Computing (MEC) will offer greater choice & opportunities
As 5G initiatives are gaining momentum across companies in Europe, manufacturers, in particular, can expect to leverage new connectivity features to improve their production capabilities. Mobile technology empowers Multi-access Edge Computing, otherwise called Mobile Edge Computing, enabling speedy access to real-time data in the shop floor, and faster decision-making across the supply chain. This high-end mobile connectivity also empowers robots, for timely connection to cloud data, and faster retrieval from the sensors.
Smart manufacturing technologies are being adopted by an increasing number of companies. An important part of implementing them is finding the right technology partner, with proven experience in the associated field. Since 2000, InApp has been a technology partner for implementing smart manufacturing solutions, and if you want to empower your business with disruptive digital solutions, we would be glad to help. Contact us to explore our solutions.