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Digital Manufacturing

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Industrial Automation

Industrial automation encompasses both factory and office settings:

In both settings, the goals of automation are similar, to improve efficiency, increase productivity, reduce errors, minimize costs, and enhance overall performance.

Digital Manufacturing

Digital Manufacturing, also known as Industry 4.0, is a computer-centered approach to manufacturing. It uses computer systems to improve machines, processes and productivity. Major systems are Manufacturing Operations Management (MOM), Product Lifecycle Management (PLM), Manufacturing Execution System (MES), and Human Machine Interface (HMI) are all integral components of industrial automation and Industrial Internet of Things (IIoT) systems. These systems support the Enterprise Resource Planning (ERP) system for manufacturing orders.




Equipment and Machines

Multiple Enterprise and Local Systems are involved in digital strategies and efforts with a focus to standardize and centralize where possible for volume cost savings and performance improvements. Here's how they work together:

MOM | Manufacturing Operations Management

  • MOM encompasses a broader set of functionalities beyond MES, focusing on optimizing the entire manufacturing operation.
  • It includes capabilities such as production scheduling, resource allocation, performance analysis, and continuous improvement.
  • MOM integrates data from various sources, including MES, ERP, supply chain systems, and even external data sources such as market demand forecasts or regulatory requirements.
  • By leveraging advanced analytics and machine learning algorithms, MOM helps manufacturers optimize production processes, reduce costs, improve quality, and respond quickly to changing market conditions.

PLM | Product Lifecycle Management

  • PLM is responsible for managing the entire lifecycle of a product from inception, through engineering design and manufacturing, to service and disposal. It helps in organizing product-related data, managing revisions, and ensuring compliance with regulations. PLM systems provide a foundation for product data that is shared across different departments and systems within an organization.
  • MOM systems typically focus on real-time control, monitoring, and optimization of manufacturing processes, while PLM systems are more concerned with managing product-related data throughout the lifecycle.

MES | Manufacturing Execution System

  • MES sits between the enterprise resource planning (ERP) system and the process control systems on the factory floor.
  • Includes Production Monitoring and Control, Quality Management, Resource Allocation and Scheduling, Inventory Management, Workforce Management, Data Collection and Analysis and Regulatory Compliance.
  • It acts as a bridge between the planning and execution stages of manufacturing, providing real-time visibility into production processes.
  • MES collects data from various sources, including equipment sensors, HMI systems, and manual input from operators.
  • It analyzes this data to optimize production efficiency, track work in progress, enforce quality standards, and provide traceability throughout the manufacturing process.

HMI | Human Machine Interface

  • HMI serves as the interface between human operators and machines or processes in the industrial environment.
  • It provides a graphical representation of the manufacturing process, allowing operators to monitor the status of equipment, control processes, and interact with the system.

  • HMI systems typically display real-time data, such as production rates, equipment status, and quality metrics.
  • With the advancement of IIoT, modern HMIs often incorporate features for remote monitoring and control, enabling operators to access information and make adjustments from anywhere with an internet connection.

PLC | Programmable Logic Controllers

  • PLCs are widely used in industrial automation to control machinery and processes. They can be connected to HMIs to provide real-time data on the status and performance of the controlled systems. The connector between HMI screens and Industrial Equipment and Machines.

Industrial Equipment and Machines

  • Controlled system examples are SCADA (Supervisory Control and Data Acquisition) Systems, HVAC (Heating, Ventilation, and Air Conditioning) Systems, Power Distribution Systems, Environmental Monitoring Systems (air quality, noise levels and emissions) and Asset Management Systems for industrial equipment health monitoring systems, predictive maintenance systems, and asset tracking solutions.

Digital Manufacturing Summary

In an IIoT-enabled environment, these systems work together seamlessly to collect, analyze, and act upon data generated by industrial equipment and processes. For example:

  • MOM uses this data to optimize production schedules, allocate resources efficiently, and drive continuous improvement initiatives.
  • MES collects data from HMIs, sensors, and other sources to track production progress and enforce quality standards.
  • HMI provides real-time visibility into equipment status and allows operators to control processes.

Overall, the integration of MOM, PLM, MES, and HMI within IIoT frameworks enables manufacturers to achieve greater operational efficiency, flexibility, and responsiveness in today's dynamic manufacturing environments.

Workflow Process Automation (example)

Consider a simple example of automating steps in a manufacturing process for producing widgets. We'll break down the process into several steps and see how automation can be implemented. Here's how automation could be implemented for each step:

Raw Material Loading

  • Raw materials (e.g., metal sheets) need to be loaded onto the manufacturing line.
  • Solution: Automated conveyor belts could transport raw materials from the storage area to the manufacturing line, controlled by sensors that detect when materials need replenishing.


  • The raw material is cut into the desired shapes using a cutting machine.
  • Solution: A robotic arm equipped with a cutting tool could precisely cut the raw materials according to predefined specifications, controlled by a computer program.


  • The cut pieces are then shaped into the required form using a shaping machine.
  • Solution: Automated shaping machines could mold the cut pieces into the required shapes based on input from CAD (Computer-Aided Design) software.


  • Different shaped pieces are assembled together to form the final product.
  • Solution: Robotic arms or automated assembly lines could handle the assembly process, guided by programmed instructions on how to piece together different components.

Quality Control

  • The finished products undergo quality checks to ensure they meet standards.
  • Solution: Automated sensors and cameras could inspect the products for defects, with machine learning algorithms analyzing images to detect any anomalies. Faulty products could be automatically diverted for further inspection or rework.


  • Approved products are packaged for shipping.
  • Solution: Robotic arms could package the finished products into boxes or containers according to predefined packaging guidelines. Barcodes or RFID tags could be applied for tracking purposes.

The entire manufacturing process can be overseen and managed by a central control system, which monitors the status of each step, optimizes workflows, and alerts human operators in case of any issues or maintenance requirements.

This automation not only increases efficiency and productivity but also ensures consistency and quality in the manufacturing process. Additionally, it frees up human workers to focus on tasks that require creativity, problem-solving, and decision-making skills.

Manufacturing KPIs (examples)  

Here are some common KPIs that many larger manufacturers track to measure their performance:

Overall Equipment Effectiveness (OEE)

OEE measures the efficiency of manufacturing equipment by combining metrics for availability, performance, and quality. It provides insights into equipment utilization and identifies areas for improvement in downtime, speed losses, and quality defects.

Production Downtime

This KPI tracks the amount of time that production is halted due to equipment breakdowns, changeovers, maintenance, or other unplanned events. Minimizing downtime is crucial for maximizing productivity and meeting production targets.

Cycle Time

Cycle time measures the average time it takes to complete one cycle of production, from the start of manufacturing to the finished product. It helps identify bottlenecks, optimize workflows, and improve overall process efficiency.

Quality Yield

Quality yield measures the percentage of products that meet predefined quality standards during production. It helps assess the effectiveness of quality control processes and identifies opportunities for reducing defects and rework.

Inventory Turns

Inventory turns represent the number of times inventory is sold or used within a specific period, typically a year. Higher inventory turns indicate efficient inventory management and can help minimize carrying costs and improve cash flow.

Order Fulfillment Rate

This KPI measures the percentage of customer orders that are successfully fulfilled on time and in full. It reflects the organization's ability to meet customer demand and maintain high levels of customer satisfaction.

Lead Time

Lead time measures the total time it takes to fulfill a customer order, from the time it is placed to the time it is delivered. Reducing lead time can help improve customer responsiveness, minimize inventory levels, and increase operational efficiency.

Resource Utilization

Resource utilization tracks the percentage of time that manufacturing resources such as labor, equipment, and facilities are effectively utilized. Optimizing resource utilization helps maximize productivity and minimize waste.

Energy Consumption

Monitoring energy consumption helps identify opportunities for energy efficiency improvements and cost savings. It also contributes to sustainability goals by reducing the environmental impact of manufacturing operations.

Supplier Performance

Supplier performance metrics evaluate the quality, reliability, and timeliness of materials and components supplied by external vendors. Maintaining strong supplier relationships and holding suppliers to high standards can ensure a consistent supply chain and product quality.

Lean Six Sigma (LSS)

LSS stands as the cornerstone of operational excellence, seamlessly integrating its effectiveness across factory and office landscapes. Originating in manufacturing, LSS has evolved into a cross-industry powerhouse, revolutionizing sectors including service-oriented offices, healthcare, and administrative processes.

In factories, LSS methodologies act as a catalyst, streamlining manufacturing processes, reducing waste, enhancing product quality, and improving overall efficiency. Transitioning to office environments, these principles optimize business processes, minimize errors, and elevate productivity. The overarching goal is to eliminate unnecessary steps, reduce variability, and strengthen operational effectiveness, regardless of industry nuances.

Crucially, LSS seamlessly complements key pillars of modern Enterprise Operations, including Process Management, Analytics, Data Management and Data Science. This strategic synergy ensures a holistic approach, enhancing our ability to make informed decisions, drive innovation, and maintain a competitive edge in the market.

Alexicion not only recognizes the significance of LSS but also employs a unique approach by incorporating insights from diverse systems and recent advancements in data science. Within the realm of business management, LSS finds a broader application, enhancing both process efficiency and analytical precision to achieve desired outcomes.

Embedded in the belief that exceptional products and services fuel customer delight and loyalty, our performance services at Alexicon reflect a management-oriented LSS approach. This involves streamlined processes and meticulous measurements, ensuring not just efficiency, but sustained profitability.

U.S. Department of Commerce - National Institute of Standards and Technology (NIST)

International Standards Organization (ISO)

ISO 9000 is a series of five international standards published in 1987 by the International Organization for Standardization (ISO), in Geneva, Switzerland. Companies use the standards to help determine what they need to maintain an efficient quality conformance system. For example, the standards describe the need for an effective quality system, regular calibration of measuring and testing equipment, and an adequate record-keeping system. ISO 9000 registration determines whether a company complies with its own quality system.

The standards define minimum requirements for quality assurance systems that directly influence product quality and customer satisfaction without suggesting tools for analysis, prioritization, and evaluation.

Six Sigma

The aim of Six Sigma is to reduce variation through statistical methods that lower process defect rates to less than 3.4 defects per million opportunities. Six Sigma focuses on putting measurement systems in place for work processes. Within these systems, Six Sigma projects identify the need to reduce variation and improve processes.

Six Sigma projects may involve anything from improving the processes involved in mass-producing component parts to completely redesigning an aircraft completion process so that the aircraft requires less maintenance. The Six Sigma methodology DMAIC (define, measure, analyze, improve, and control) is the system for improving existing processes that fall below specifications and need incremental improvement. DMADV (define, measure, analyze, design, and verify - sometimes referred to as Design for Six Sigma [DFSS]) - is used to develop new processes or products at Six-Sigma-quality levels.


Lean is a series of tools and techniques for managing your organization's processes. Specifically, Lean focuses on eliminating all non-value-added activities and waste from processes. Although Lean tools differ from application to application, the goal is always incremental and breakthrough improvement. Lean projects might focus on eliminating or reducing anything a final customer would not want to pay for:

  • scrap
  • rework
  • inspection
  • inventory
  • queuing or wait time
  • transportation of materials or products
  • redundant motion

Lean-focused organizations extend the concepts of waste elimination and value-added processes to suppliers, partners, and customers. At full potential, all aspects of a Lean organization's value chain have eliminated waste and are operating at full value-added potential.

Enterprise. Orchestrated.