By:  Jijnasa Panigrahi & Arun Yadav, Helium Consulting

In this era of agile and smart manufacturing, quick and accurate access to plant data is crucial. This is to ensure that the manufacturing plants are constantly responding to changes in the market place, available feed stocks, inventory position and other supply chain requirements. In this article we would talk about a critical item – Plant Data- and how it is used- that can convert the plant from being a bottleneck in the supply chain to a strategic asset. Plant data availability at the right time and place has been made possible with software and IT enabled services. From public viewing of plant data in local computers to excel files to dashboards to personalized viewing in mobile devices, software solutions have made it possible to see and act upon plant data in dynamic manufacturing space. Manufacturing industries are inclined towards achieving manufacturing excellence, but the downside in achieving this is lack of clear visibility of manufacturing data.

Manufacturing data is very important for taking precise decision. There are lots of software’s available in the market for capturing the plant data and historizing it. Through this article we would share with you five simple ways that is programmatically achievable today to implement without spending a fortune.

Although all these software’s work independently, for providing an overall visibility, we can integrate all these software on a common platform like a dashboard. The dashboard is a placeholder where a shop floor data from plant is displayed on computer systems and mobile devices with clarity & prominence. While proliferation of data availability has been very good in the industry – it is the challenge of keeping it real time and accurate along with easy access and filtering that has plagued the industry in general. With this introduction to the manufacturing software domain we have listed the top five ways to keep your plant data accurate.

Plant data management system would cater to various requirements at different levels of the organization like Operation, Lab, R&D, Management, Senior Management etc. Every layer has its own requirements which are very diverse and thus need access to industry data which are presented in different report in different forms. Data security is also a crucial part of this technological advancement which has been implemented across in different layers to insure data security, integrity and access control. This paper will discuss the five layers of data management and reporting at different level, its yield and benefits in any industry.  It’s good to have all the five ways for better data management, progress of the business, better decision making. The first and most important layer is the Data historian layer. This is the base layer in any data management system. The day to day plant operation needs this data to monitor the plant. The Lab and R&D team need the records of samples and lab results. The operation needs this data to monitor if the operation is going on properly or not. The Management layer needs access to data like the plant performance data and other key process parameters. The top most layer and senior management would want to see the summary of all these data in one place for analysis and decision making, it can be further advanced by providing mobile accessibility to this data to stakeholders as it would allow them to access this information as per their requirement on the go.

1.Historizing Process Data
Effects of introducing the Layer: A process historian system would primarily capture plant data. This system directly communicates with the DCS or any other automation system like PLC/SCADA which then collects and stores the data and would make it available outside the control room.

Upshots: Any process engineer or plant operator can access this real time plant data from his or her PC / Laptop and can have a balanced idea about the plant operation available at the click of a button. With this data a process engineer can perform on the fly process calculations and store them for viewing by others.  Recent developments in these tools have led to use of process analytics like SPC and OEE which provides a clear visibility of the plant performance.

More graphical features have been added to this system which delivers a graphical view of the plant operation like that in DCS. This whole advancements and tools have enabled the process engineer and plant operator to take prompt decision in terms of control and optimization.
Benefits: With this system companies can integrate its entire plant in one place and can centralize the process data bank. This system would be further useful for generating automated plant operation report and other important reports which would add value to the overall plant performance.

2.Instrument and Maintenance
Effects of introducing the Layer:  Availability of quality data from QC/QA lab is very crucial for a manufacturing plant for decision making and for controlling the process conditions. Most of the Indian manufacturing companies are paper based and spends a lot of time in gathering lab data.
Upshots: Many manufacturing software consultancies offer wide range of solution for LIMS (Laboratory information management system). With this system we can collect laboratory information directly from measuring instruments and store it in a database.
Benefits: These data are used for immediate access to quality information and for automated calculations, which are displayed for viewing on dashboard. These systems are very useful for maintenance and for measuring reliability of instruments and other measuring equipment.

3.Business & Operational Alignment with KPI and key Metrics
Effects of introducing the Layer:  People within the organization are unaware of the business objectives or goals that are pursued at the Management level and how these goals or objectives get affected by various routine activities performed at the operational level. For example, if an organization has made heavy investments in equipment they will be more inclined to measure the ROI at the management level. They need to eventually measure equipment at the plant level. This in turn means a close check on the availability (downtime), quality and performance of the equipment. Hence, these parameters need to be monitored and controlled at the operator or supervisor level in order to meet the business objective at the management level

Upshots: Benchmark KPIs should be defined along with KPI trees at different operational levels to provide performance visibility. Drill-down capabilities should be provided in order to get to the problem areas that are affecting the KPIs.
Benefits: A score carding system (perhaps based on a balanced scorecard approach) can be very effective in making performance visible, thereby forcing an emphasis on visibility of performance targets and actual performance and encouraging an environment of increased accountability. We have developed industry specific analytics engines to acquire, transform and analyze the data.

4.Performance Visibility through Dashboard

Effects of introducing the Layer: Once the integration, is achieved, the next important aspect is getting the data analyzed, aggregated from multiple systems and delivered to the right person at the right time.
Upshots: This would not only give the user actionable data through which various events, workflows can be triggered, at the same time it empowers the users to take real time decisions for the shop floor based on exact factual data.
Benefits: Role-based dashboards for operators, supervisors and plant managers will provide them with accurate optimum data for enhanced decision support.

5.Mobility of process data
Effects of introducing the Layer: In the past, users needed to be in the control room or in front of a monitor to track and manage manufacturing performance. With the use of mobile based applications, that same manufacturing performance data is now available regardless of a user’s location, enabling key decision makers to access information earlier in the process to make faster and better informed decisions.
Upshots: Mobile applications deliver process data in a way that allows companies to improve business processes from the operational level to the executive management level. The data can be viewed in value fields, trends, reported by exception, or accessed in KPIs.

Benefits: Expanding the accessibility of critical manufacturing data improves employee effectiveness and supports continuous improvement efforts and manufacturing excellence goals.

Key Benefits for manufacturing industries from the above mentioned five ways:
1. End to end visibility into operations
2. Ability to take action for events and Create a world Class Manufacturing environment
3. Apply Operational Excellence measures and Implement Actionable Six Sigma Initiatives

And all this at an investment that does not burn a hole in a Manufacturer’s pocket and justifies a quick ROI!