Driving Performance with Digitalized Manufacturing - Dell Smart EQM
At a glance
Focus: Driving Performance with Digitalized Manufacturing – Dell Smart EQM
Challenge: Dell faced a static quality audit approach relying on a fixed sampling plan, manual processes, and potential bias — with a risk of missing daily sampling targets — creating an opportunity to develop a closed-loop, dynamic quality audit system instead.
Approach: Following opportunity and challenge analysis, design thinking brainstorms identified a data-analytics solution combined with IoT functionality as the optimal approach — moving through problem definition, alternative evaluation, rapid prototyping, piloting, and finally live deployment at the first site followed by global rollout, with an in-house collaborative team spanning Engineering, Quality, and IT.
Impact: The solution delivered improved outgoing quality and process efficiency with improved productivity, achieved through a Data Analytics engine that dynamically updates sampling plans and a conveyor-line PLC integrated with the analytics engine to identify and divert units for real-time quality audit.
Dell International Services India Pvt Ltd
Dell Technologies provides customers of all sizes – including 98 percent of the Fortune 500 – with a broad, innovative portfolio from edge to core to cloud. Dell Technologies provides wide-ranging technology solutions including Dell client as well as Dell EMC infrastructure offerings that enable organizations to modernize, automate and transform their data center while providing today’s workforce and consumers what they need to securely connect, produce, and collaborate from anywhere at any time.
Business challenge
The following challenges were faced that led to the discovery of the problem -
Static quality audit approach with fixed sampling plan based on manual processes and potential bias.
Opportunity to develop actual closed-loop quality performance with sampling plan to create a dynamic audit approach.
Risk of missing daily sampling plan, led to definition of automated solution.
Opportunity to improve output quality with an automated closed-loop audit approach.
Potential process efficiency with enhanced automated selection.
Industry 4.0 solution
Key steps involved in going from ideation to decision
Opportunity and challenges analysis (as above) led to Design thinking brainstorms on alternative solutions.
Data-analytic solution combined with Internet-of-Things (IOT) functionality was identified as an optimal solution.
Defining problem statement and opportunity analysis
Alternative approaches identified and evaluated
Converge to optimal solutions
Rapid proto-typing
Pilot
Live deployment at first site and followed by Global deployment
Resource allocation and structure
In-house collaborative team approach involving representatives from Engineering, Quality and IT teams was followed for working on the solution deployment.
Change management
The solution was deployed in a phased manner with opportunities for review and refresh course:
Phase 1 focused on physical automation for sample selection
Phase 2 focused on developing analytical engine for sampling plan
The change management issues were tackled through -
Early engagement by all internal teams, continued throughout process.
Training identified and provided for team members facing a change in responsibilities
Data Analytics engine analyses actual quality performance for each model and dynamically updates the sampling plan.
Conveyor line Programmable Logic Controller (PLC) integrated with analytics engine identifies units for audit and diverts to quality audit station in real time
Leverage Dell products and services to develop analytics engine & IOT components of the solutions.
Key benefits
| Area | Outcome |
|---|---|
| Quality | Improved outgoing quality |
| Productivity & Throughput | Process efficiency with improved productivity |
Technologies used
Change management and implementation
The following risks were foreseen while embarking on solution development -
Technical (Low risk)
Barcode scanning of units at varying orientations and in motion on conveyor
PLC logic integration with analytics engine
Assuring analytics algorithm and right-time data refresh
Financial
Medium-level investment for hardware and software components
The technical risks were mitigated through iterative process, refinements after each version and financial risks were mitigated by leveraging in-house resource and hardware.