Downtime – Biggest Challenge in Manufacturing Industry
According to a detailed analysis conducted by technology market research firm Vanson Bourne, around 82% of firms experienced at least one unscheduled downtime interruption in the previous three years. At least two were the average.
Furthermore, according to a study (Aberdeen), an hour of downtime can cost up to $260,000, which has increased by 60% since its last published data in 2014, which was $164,000.
During such downtimes, many hidden costs are incurred that many businesses fail to assess appropriately. This makes it critical for manufacturing organisations to abandon outdated monitoring methods and capitalise on the most recent improvements in equipment and technology. Effective technology installation at the right moment can considerably reduce such expenditures.
Journey of Manufacturing Companies:
With Industry 3.0, manufacturing companies introduced computers into their processes. SCADA systems were deployed for Supervisory Control and Data Acquisition for large-scale manufacturing. The data collected and processed by these systems were used to make proactive decisions and optimise their processes.
These SCADA systems were installed on their central servers and were monitored and maintained by their IT team.
Problems with these Solutions:
The list is lengthy, so let’s take a brief look at some significant issues:
- Scalability – These systems could not be scaled. As the number of users increased, so did the performance. Data retrieval from remote servers took longer.
- Data Analytics and Insights – These systems only saved finite amounts of data and made little use of historical data for analytics.
- Standardization – Traditional systems relied heavily on OPC.
- Interoperability/Interconnectivity – Solutions from one vendor were incompatible with those from other vendors. This resulted in the dilemma of sticking with the same manufacturer despite displeasure and not combining data from several devices to derive patterns.
- Infrastructure Costs – With increased storage expenditures and upgrade costs, infrastructure costs were high. Maintaining these installations required investments in human resources which were quite expensive.
- Data Accessibility – Data kept on on-site servers could only be accessed within the company’s walls. Getting access to the data required some approval from the higher level in the organization which hindered the data accessibility and took a longer time than expected.
Continuous improvement is the principle of life. The monitoring and controlling solutions continually improved and adapted to the industry needs.
Industry 4.0 brought in the concept of IoT (Internet of Things).
The above challenges got resolved mainly by moving on to Cloud-based solutions. How? Let’s see:
- Scalability: Its serverless architecture enables on-demand scalability, and it can ingest and handle massive amounts of data from linked sensors/devices. One of the most significant benefits of using the cloud is simple and very scalable. Scaling up sophisticated local network infrastructures necessitates purchasing more gear, devoting more time, and completing additional setup tasks to ensure proper operation. It is, however, a cloud-based system; adding extra resources usually requires launching another instance or adding more cloud space and does not necessitate any upfront or long-term investments. Scaling down and limiting storage requirements is as simple as scaling up.
- Data Analytics and Insights: IoT involves long-term data retention to analyse the data further to predict maintenance schedules, reduce overall downtime, and extend equipment life. The world is shifting from Condition-based Maintenance to Analytics-and IoT-enabled PdM (Predictive Maintenance)
- Standardization: The solutions are based on open standards with support for MQTT, HTTPS, RAML etc.
- Interoperability/Interconnectivity: Protocols such as MQTT allow communication of different vendors’ devices. This allows connecting anything like vibration sensors, flowmeters, temperature sensors, occupancy sensors etc., to Cloud and processing all the data together and deriving trends across these.
- Infrastructure Costs: Cloud services significantly mitigate the software and hardware costs. Now companies can focus on their primary business rather than worrying about the servers, connectivity, etc.
- Data Accessibility: With Data in Cloud, it is accessible from almost anywhere globally with security handled efficiently.
The simplicity and low cost of implementing and maintaining these solutions due to Cloud technology are turning more and more companies towards these cloud technologies. They have started realising that a suitable investment today will help them save thousands of dollars by preventing unplanned and unforeseen downtimes.