Transformation of manufacturing process is a crucial component for global competitiveness. Today, most large organizations explore new technologies such as IoT, Machine Learning, Cameras, 5G and new generation software to transform their manufacturing systems.  This digital transformation journey has many worthwhile targets, encompassing self-adapting factories, autonomous material handling and logistics, cognitive supply chains, IT-OT convergence and sustainable manufacturing. Despite the availability of technology for implementing,  transitioning from pilot to tangible business benefits poses challenges, including resourcing issues, master data issues and cost of scaling. As a leading global technology provider, we have developed an MES-centric methodology to validate business value during the planning, operation and post implementation stages of a digital transformation initiative.

An Architecture for Business Value

Overcoming barriers to business value improvement initiatives today involves integrating supply chain, manufacturing, engineering R&D and employee experience and knowledge through a common digital thread. This enables both vertical and horizontal integration, paving the way for enhanced value creation. To design a reference architecture that leverages this thread for digital manufacturing, we map the ISA95 enterprise stack to the Purdue Model. We further refine this architecture to accommodate smart manufacturing solutions, such as optical quality monitoring instruments and linkages to smart sensors. (Figure 1).

At the heart of this architecture is Manufacturing Execution System (MES) software, automating standard MESA functions like scheduling, resource allocation and order dispatching. Modern MES systems like the Critical Manufacturing MES offer separate modules for these functionalities.

Integration through such an MES platform is an imperative for digital transformation. In our reference architecture, the ISA 95 and Purdue upper tier ERP, PLM and other transaction data flow into the MES from the top of the enterprise, while equipment and process data originate from below. This architecture has facilitated business value creation and operational improvement across various verticals.

Defining Business Value

Nearly every digital transformation initiative in manufacturing aims to enhance at least the following business value improvement objectives.

  • Overall Equipment Effectiveness (OEE), which might improve with the help of predictive maintenance activities, is measured as increases in utilization rate or reduction of downtime.
  • Product quality improvements, steps might be taken to enhance first pass yield or reduce rework through compliance enforcement, as measured by defect reduction.
  • Improved operation efficiency, expressed by a reduction in variable costs.
  • Inventory optimization, achievedthrough planning and space utilization management, demonstrated by reduction in material inventory holding costs.

Since the MES extensively connects various areas of the business, calculating business value requires data collection from all corners of the enterprise including assets, processes, applications and people.

HCLTech’s Roadmap to Business Value

Our process begins with a comprehensive pre-survey encompassing the review of plant assets, production process, applications, incoming data and workforce, validated through on-site visits. Subsequently, we meticulously analyze this data to figure out areas with the highest potential for impactful improvements. This includes scrutinizing process and systems gaps within each of the 11 MESA categories, translating them into KPIs and use cases. Each identified gaps undergoes evaluation according to its impact on business value and the associated cost of closure. that gap, based on data analysis, product knowledge, domain experience, vendor input and research. Furthermore, we determine which gaps that can be addressed by out-of-the-box software solutions and which need custom applications.

Weighing the significance of each gap closure to profitability and the expenses required to close it, we ascertain which improvements would offer the most immediate ROI. Recognizing the limitation of not being able to do everything at once, we implement the changes in two or three phases to maximize efficiency.

Connecting the Threads

The model provides a logical flow from target KPIs to quantified business benefits, such as increased productivity, incremental revenue and reduced defects.

Establishing a clear link between process and system gaps, KPIs, use cases and quantifiable business benefits, will be crucial for securing buy-in from senior management, plant management, operators and other stakeholders. In addition to helping to secure resources for the project, having a detailed road map will guide implementation and shorten the time to benefit.

For more details on planning and implementing an MES-centric strategy that will turbocharge your manufacturing operations see: Shantanu Rai, Supercharging Manufacturing Transformation | MESI 4.0 Summit, 2023.