Connecting the Digital Thread Across the Quality Lifecycle

In the world of the digital thread, a heavy emphasis has been placed on connecting research & development with manufacturing and then to the supply chain. Quality management has often been pushed to the side, largely due to regulations and the traditional use of disparate and disconnected systems to track and manage the quality programs. Over the years, connecting the outputs from various quality issues and events has been difficult. Most data are integrated to different business intelligence (BI) tools or exported to a data lake for analytics, producing poor reporting against the products. The primary reason is that quality issues and events are rarely tied to a Bill of Materials (BOM) structure and/or to the individual part that make up the finished goods.

Why is that?

Quality systems don’t have concepts of a BOM structure, although most will be capable of importing a list of finished good SKUs to associate quality processes like CAPAs, complaints, nonconformances and audits. What about other systems outside the general QMS? Do these systems have the same SKUs? Where are the finished goods and parts managed?

The answer is your global PLM system, where change management is executed, the full digital product definition is outlined, and product families and variations of the same parts and products are managed. Integration of quality systems to PLM leads to a closed-loop quality management system which will not only streamline your multitude of processes to one central location, but it will also alleviate the burden imposed on quality resources during a quality event. Further, it will also improve an organization’s control of processes and significantly lower their Cost of Poor Quality (COPQ) budget.

The digital thread cannot be achieved without connecting all the quality issues and events across an enterprise to the digital parts managed within a PLM system.

This is where a paradigm shift is happening for companies that have invested in a digital product definition and linking these issues and events to the appropriate parts that make up the definition. Digital product quality (DPQ) provides the enterprise solution to take these issues across an enterprise and relate them to the parts and product definitions managed with PLM.

Below is the DPQ solution framework connecting quality issue intake systems across an enterprise to the digital product definition managed within PLM. It then provides a solution for collecting these issues for evaluation by a quality product subject matter expert to disposition one to many against a continuous improvement process (CIP) within PLM or to an external system creating full traceability across the digital thread.

Kalypso’s Digital Product Quality Solution

Three core value drivers are pushing this paradigm shift within the digital thread:

Traceability

Initiating quality issues against a part or product creates a digital history of events that can be viewed by R&D, global quality and manufacturing. Multiple issues can be evaluated, initiated, and linked to a single (or multiple) Continuous Improvement Processes (CIPs) within PLM or to external systems like QMS or MES. The digital product definition managed under enterprise change also has traceability and connectivity to the CIPs. This leads to increased transparency throughout the change management process. With increased traceability against the parts, products, and issues, Quality can determine where there are opportunities to leverage CIPs not only for the current part, but also for variations of the same part. With greater efficiencies and a reduction in redundant CAPAs, the process moves away from a documentation exercise and focuses on collaboration and continuous improvement, more closely aligning with the original intent of the ISO 9001 standard.

Enterprise Visibility

Most large enterprise organizations struggle with global visibility as it relates to their products and their associated quality processes by consolidating all quality issues and processes with respect to the digital part/product definition, anyone who has access to the global PLM system can view this data in real time for the parts/products of their expertise. Many enterprises manufacture the same products and parts across the globe. The same issues affecting one region can be easily seen by other regions to understand if a global change is required, or if the issues are isolated. This visibility leads to greater collaboration and improves the speed to market for next-generation products by consolidating the efforts required for the change management process and empowering enterprises to understand the core issues with parts, products, and suppliers in the field.

Data lakes are great for advanced analytics and business intelligence, but if quality issues, events, and processes are not related to the appropriate finished good or part managed in the PLM system, then significant work is required to pull this data together. Quality engineers spend a large portion of time trying to consolidate information from various systems to determine how to investigate root causes and establish corrective action plans to remediate the problem.

Predictive Analytics

By completing the digital thread and relating quality issues and processes to the digital product definition, a foundation is created to drive predictive and prescriptive analytics. Machine learning focusing on the digital part or finished good can start to interpret what events are happening in each region along with what events or outcomes can be expected. A company can then move to risk-based continuous improvement by evaluating the biggest risks to their products, patients, and brands and taking proactive measures before they become mission-critical issues across the enterprise. Change management can then be linked to the prediction model to initiate, escalate, and formulate the appropriate actions as part of a global enterprise change for the parts/products reducing speed to market and helping drive next-generation products to the market faster.