The integration of Quality 4.0 with Industry 4.0 is a daunting task for many organizations let alone quality professionals. Historically, "Quality" has not been viewed as a discipline that embraces technology like that of Industry 4.0. Management relies on the Information Technology (IT) or Operational Technology (OT) departments to solve problems. In most organizations IT handles administrative data and processes; e.g., accounting, purchasing, sales, and marketing while OT handles process data; e.g., sensors, robotics, artificial intelligence. Quality professionals need to break management's view that "all things data belong to IT or OT". Quality professionals have an opportunity to embrace technology and data at a grass roots level by learning about Big Data, Advanced Analytics and Data Science as it pertains to products and processes to improve customer experiences. This workshop will focus on building toward a collaboration of quality professionals with various other disciplines in an organization to embrace technology and its value to making data more available for making and implementing better, more consistent decisions. Participants will be exposed to technology available with the Industry 4.0 and Quality 4.0 disciplines to build a better understanding and framework for their organizations. The key that will be presented in this workshop is how quality can lead a collaborative effort. This collaborative effort melds subject matter experts from various disciplines to build a strong collective knowledge. Examples of Big Data, Advanced Analytics and Data Science will be presented to assist participants to see which tools and techniques best fit their organization. From these examples, participants will integrate the appropriate tools into a roadmap that they develop for their organization. Participants will evaluate both the strengths and opportunities for improvement for each discipline. They will then evaluate their organization to maximize strengths and build plans to address opportunities for improvement. Management oftentimes throws problems "over the wall" to IT or OT and expects "magic" to come back. It is not fair to expect IT/OT personnel to understand all facets of: 1) what data needs to be collected, 2) where to store it, 3) how to format it and 4) to whom to grant access for success. Additionally, in many cases they are unfamiliar with what should be the best analytical software to evaluate data to solve the problem. Since they are the individuals with the budget and confidence of management, they feel obligated to “solve the problem”. Quality professionals are in a unique position to understand products and processes from a broader perspective. This perspective will be integrated into a plan to give a path to create the collaborative necessary to ensure higher success rates in getting problems solved in a better, more consistent fashion in the decision-making process. The process for quality professionals entails understanding data science. This presentation will outline four categories of “data scientist” from the very technical aspects of high volume, high velocity, high variety data all the way to ensuring that the final reports and decision implementation are optimal for the organization. Participants will identify individuals in their organization that they feel “fit” each of data science categories. This will give participants not only a view of "what" needs to be in the plan, but also ideas for "who" may be the best person(s) for the responsibility. Through their plans and leadership, they can make valued recommendations for their organization. Integrating Quality 4.0 with Industry 4.0 will not be successful if left to isolated disciplines like IT, OT, engineering or even quality. There is no one person or discipline that can, nor should, “do it all”. Participants will see the necessary talents and how they can be integrated for a true integration of Quality 4.0 with Industry 4.0. A roadmap will be created, from examples, showing the parallels between historical approaches along with those of more modern Smart Manufacturing systems. The objective of this workshop is to assist quality professionals to understand the tools necessary to successfully integrate Quality 4.0 with Industry 4.0 and Smart Manufacturing and build a plan that fits their organization while optimizing the talent available as well as identifying talents that need to be acquired..
Learning Objectives:
Identify the items necessary to integrate Quality 4.0 with Industry 4.0 for their organization from examples given
Create a list of key measures that includes identification of availability and access to data as they see it in their current environment then attach shortcomings in the current system that needs to be addressed.
Create a list of analytical methods that best fit key measures that includes data formatting and type of statistical software for analysis
Create a list of individuals and the associated data science attributes for maximizing talents and identifying training and personnel gaps.
Complete a roadmap for their organization for creating a collaborative to optimize data and decision-making