Change management and mindset management#SmartManufacturing #Scalability #Operationalexcellence #Nanoprecise
As far as execution is concerned, the digital transformation initiative needs to be driven from the top and the buy-in should be established from the end user. As far as technology is concerned, there is a need to initially ensure the basic level of automation as well as a need to focus on enhancing the data collection and having a data maturity level.
The third edition of the Pro MFG Technology Leadership Think Turf ‘Let’s Talk Scalability series’ powered by Nanoprecise Sci Corp focussed on ‘Smart Manufacturing and Operational Excellence’ in the context of the chemicals industry. This engaging fireside chat witnessed three esteemed industry speakers in Chetan Joshi, Head Continuous Improvement & Digitization, Tata Chemicals, Sandip Chakraborty, Sr. VP- Operations, Aarti Industries, and Prashant Verma, Co-Founder and Product Lead, Nanoprecise Sci Corp. The discussion was steered by Ravi Rama Rao, Chief Architect & Trusted Advisor Digital Transformation & Manufacturing Excellence.
It is said that digital transformation is a journey and it has several elements to it. Could you shed light on the prioritisation of what to focus on first?
Chetan Joshi: Surely, digital transformation is a journey and it has several elements and many objectives. Organisations can do prioritization by carrying out digital value assessment of the probable plant use cases by collecting the past historical data of sufficiently larger duration and arriving at the current baseline. They can identify the amount of variation that exists in the current process and find out what are the possible opportunities for improvement. Organizations also need to find out the maturity of automation and sensorization. So, prioritization can be done based on the cost, effort and benefit metrics.
As far as execution is concerned, the digital transformation initiative needs to be driven from the top and the buy-in should be established from the end user. Capturing the voice of the end user voice is also very much necessary. Change management and mindset management are equally critical for the success of this type of initiative. As far as technology is concerned, there is a need to initially ensure the basic level of automation as well as a need to focus on enhancing the data collection and having a data maturity level.
What are the ideal metrics for optimisation- specifically for setting the right KPIs? How do you align your metrics with your organizational goals and operations?
Sandip Chakraborty: In a plant, there are multiple input data as multiple output data. However, only some data is relevant and a combination of the data is relevant. So, you can make soft KPIs and then monitor the performance of the equipment or the plant based on the soft KPIs. Then you can go to the digital twin where the digital twin will give you predictive models. It can integrate the operating parameters to develop statistical models using different languages. This can be used to integrate operational data and process parameters to determine useful KPIs through which you can monitor the plant performances. In future, we can go to the prescriptive where through machine learning this digital data can also be prescriptive. In fact, first it can predict whether the machine is running with the right efficiency or not, or whether a breakdown is going to happen, or whether some pump is going to behave in a different way because past data shows that this parameter has affected the operation of the equipment. It can slowly go to prescriptive models where it can say that you grease the motor bearings or you reduce the flow or you clean the heat exchanger of a distillation column or something like that. So these are the journeys that we can slowly move from descriptive to prescriptive models. So, this is the journey which the industry is now embarking on. I believe it will take at least four to five years for the industry to achieve maturity and get the right results from it.
Right now, we are generating data at different points in different forms and in different areas. So digital can really bind all the data and help you bring it in one area. At the click of a button, you can have all the data available with you. Secondly, with many sources of data, there can be conflict of truthfulness. So digitization should help in providing truthful data irrespective of the sources. Thirdly, digitalization can help in efficiency improvement as well as in problem solving. It should help you do things right the first time. So, the problem you have solved should not get repeated.
What are the main reasons behind many digital transformation programmes not going beyond the pilot stage? Is it the time required, is the efforts required or is it the resources required that become a deterrent?
Prashant Verma: It is true that digital transformation fails 80% of the time. The most important reason that I see is not having clarity about the objective behind the transformation. The term transformation implies that we are transforming something - in this case, we are doing it digitally or by using some technologies. So, first of all, we should define the problem statement; this is very important. Digital transformation can be applied to many places and in many areas. Let’s take an example: Let’s say we need a reduction in breakdown to 60%, reduction in the unplanned downtime to be 35% to 40%, and reduction in the maintenance cost by 45%. Now, we have the KPIs and the problem statement is very clear. The second step would be to log the information or data from wherever it is coming. The data can be from the DCS or some sensor devices or even from some written documents. Once we have the data, then we start doing some analysis. That would be the second step. When we talk about this problem statement, many times or almost all the times, we see that the digital transformation programme is at the board level. But they forget to convey the mission and vision of this programme to the ultimate end user. This failure of change management can lead to reluctance in the shift of the company culture. And that is very important for digital transformation. Digital transformation is not a technology; it’s the mindset or a process. It cannot be treated as a destination, it is a journey. And every journey starts with small steps. In this journey, having the right partners is very important. Right partners means partners who understand the end user. If the partners do not understand the end user, they will not have any kind of service or product which has good user experience. If we talk about the design thinking philosophy, empathy is the first step. So any vendor or any partner in technology should be well aware of the end user requirement. So many times digital transformation fails because people are not able to scale up or the end user doesn’t understand the technology or the service itself.