Big Data Tools and the Internet of Things
Introduction
Manufacturing corporations are going through a paradigm transformation from automated manufacturing to smart manufacturing. In the course of this transformation, the Internet of Things (IoT) plays a significant role in linking the physical manufacturing environment to the computing platforms’ cyberspace and algorithms of the decision- making. As a result, this forms a cyber-physical system (CPS) (Dai et al., 2019). Internet of things analytics is the assessment of enormous data volumes that are produced by connected devices. Firms can obtain numerous benefits from the internet of things. Companies get various benefits from IOTs. However, there are also many limitations of IOTs. The paper below discusses the benefits and challenges associated with Big Data Analytics for Manufacturing Internet of Things.
Benefits
One of the benefits is the IOT data value for firms. Various devices connected to the internet and consequently engage in data sharing through sensors. The data loses value in the absence of analysis. Nonetheless, with a solution of IoT analytics put in place, the generated data by companies is successfully collected, assessed and stored. Consequently, this permits firms to boost their operations at each phase, attain numerous benefits and enhance decision making. IoT data increases the productivity of humans. Some companies implement smart sensors all over their facilities to gather data on the performance ratings, employee engagement and other work-correlated activities (Khvoynitskaya, 2019). The data is afterwards used in enhancing the everyday operations of business and help in the effective use of employee energy and time. IoT data analytics can have a positive impact on the productivity of the employees and the overall success of the business if it is assessed and employed effectively.
There is enhanced maintenance of the equipment. IoT sensors and data analytics combination helps firms, particularly in the manufacturing industry in determining when equipment needs maintenance through the measurement of heat, vibration and other crucial figures. IoT permits employees to have a clear view of the machines’ performance in actual time and subsequently alerts them in real-time to any arising issues. Having the ability to avert unscheduled downtime by utilizing analytical maintenance can offer crucial benefits. Operations automation and optimization is another advantage (Khvoynitskaya, 2019). With the internet of things and analytics working together, companies can have automatic control of the processes that in the past, could not be tracked physically. For instance, it offers manufacturers a universal view of the activities at every production point, which permits them to maintain constant final products’ flow, pinpoint barriers in actual time and avert defects. It also mitigates human error risk. Various manufacturing companies such as Bosch Rexroth saw a significant productivity surge of both equipment and employees when they started using IoT.
IoT also provides enhanced consumer experience. Each firm aims at creating an enhanced and personalized consumer experience regardless of the industry. IoT data analytics implementation aids with challenging tasks. Besides, IoT data discloses a wealth of client preferences and behaviours, which can be assessed and used in the prediction of consumer needs. For instance, in the healthcare industry, hospitals can use actual time IoT analytics of data in the management surging patient traffic and subsequently enhance the overall efficiency of operations. As a result, this is beneficial to the involved parties. Customers obtain increased value through time-saving and convenience. Companies, on the other hand, increase their revenues and maintain their appeal to their clients.
Challenges
There is a significant challenge in the big data analytics for IoT as a result of the heterogeneous structures, tremendous volume and the increased dimension. Various significant challenges include MIoT is temporally and spatially connected. Management of the data and extraction of useful information from the temporally linked MIoT presents a considerable challenge. There is also a challenge in the designing of effective schemes of data mining since there is no feasibility in applying traditional multi-pass schemes of data mining as a result of the enormous data volume. It is also crucial to reduce the uncertainty and errors of data as a result of the erroneous MIoT data traits (Dai et al., 2019). Further, even though numerous conventional privacy-preserving analytical schemes of data exist, they might not be relevant to the MIoT with the heterogeneous structures, large volume and Spatio-temporal connections. Thus, novel privacy-preserving systems of data mining should be employed to solve these challenges.
Additionally, numerous organizations do not obtain value from their assets of data since they do not have technical knowledge. Besides, employees at times get overwhelmed with the data amount coming in, which prevents them from sieving through the data and finding effective ways of using it (Khvoynitskaya, 2019). There could be a consequent data overload for the equipment or the employees with various sensors offering information frequently if the right ones are not being utilized. Other prospective challenges to the adoption of IoT analytic encompass issues of security and increased expenses. If one system goes through a breach of security, there is a higher likelihood that it will spread all over the systems, since it needs multiple devices and machines working collaboratively and exchanging information. Besides, the costs of implementation can be high since IoT data analytics is objectively new. This can prevent industries from adopting it, particularly if it becomes a challenge to see gains of investing in the long term.
Conclusion
The paper discusses the benefits as well as big data analytics’ challenges in manufacturing the internet of things (MIoT). For instance, data is used in the enhancement of the day to day company operations and also assist in effectively using the time and energy of the employees. Besides, the combination of IoT sensors and data analytics helps companies primarily in the manufacturing to determine the maintenance of the equipment through measurement of factors such as heat. However, various challenges, such as data management and valuable information extraction from the temporally connected, exist. Nonetheless, even though significant problems still exist, the popularity of IoT data analytics is on the rise. IoT has the capability of providing unparalleled insights that have never been accessible in the past. Overall, it is highly likely that big data analytics will play a significant role in nurturing the manufacturing industry to develop into useful manufacturing in the predictable future.
References
Dai, H. N., Wang, H., Xu, G., Wan, J., & Imran, M. (2019). Big data analytics for manufacturing internet of things: opportunities, challenges and enabling technologies. Enterprise Information Systems, 1-25.
Khvoynitskaya, S. (2019). How Can Your Company Benefit from IoT Data Analytics. Retrieved from: https://www.itransition.com/blog/iot-data-analytics#:~:text=Simply%20put%2C%20IoT%20data%20analytics,more%20customers%2C%20and%20empower%20employees. Accessed 9 July 2020.