Seabrook Academy

MES/MOM Overview

1) Functional Introduction

A manufacturing execution system (MES) is an information system that connects, monitors and controls complex manufacturing systems and data flows on the factory floor. The main goal of an MES is to ensure effective execution of the manufacturing operations and improve production output.

2) Process/Ops Impact

An MES has a process/ops impact by tracking and gathering accurate, real-time data about the complete production lifecycle, beginning with order release until the product delivery stage for finished goods.

3) Compliance & Quality

The MES collects data about product genealogy, performance, traceability, material management and work in progress (WIP) and other plant activities as they occur. This data, in turn, allows decision-makers to understand the current settings of the factory floor and better optimize the production process.

4) Project Justification

An MES is often integrated with ERP, supply chain management, product lifecycle management and other key IT systems. A key benefit of using an MES includes:

  • Increased customer satisfaction
  • Improved regulatory compliance
  • Better agility and time to market
  • Improved supply chain visibility
  • Reduced manufacturing cycle time
  • Elimination of paperwork and manual data-entry processes
  • Reduced order lead time
  • Lower labor costs
  • Reduced WIP inventory
  • Increased machine utilization

Operational Excellence

1) Advancing through the Mfg. Maturity Model

Ideally, the maturity model has helped determine where your systems are positioned in the maturity lifecycle. After knowing the “what” of the maturity model, focus then turns to the “how”, that is, how a company can overcome the hurdles to move up the maturity model.

2) MES Readiness

The goal of MES readiness is to, based n business objectives and drivers, evaluate the readiness of individual units to contribute to and benefits from MES/MOM.MES/MOM systems touch many aspects of the manufacturing operation and support organizations. The impact and projected ROI of an MES/MOM on an organization must be addressed from many perspectives, as it’s not just a technology solution.

  • Analyze, assess and document potential MES requirements from four different perspectives – Business, User, Process and Technology
  • This better defines the potential cost-benefit of a MES/MOM solution (ROI)
  • Increases the consistent adoption of the MES/MOM across the organization
  • The end result is the evaluation of individual units to contribute to and benefit from MES/MOM

3) Using MES to Drive CII

Solution Best Practices

1) Global MES Infrastructure Best Practices:

Utilize the below best practices to get your MES selection right, the first time:

  1. Define Business and Project Goals – what do you wish to achieve from implementing an MES solution.
  2. Assemble the Team – The team you put on the project from selection to implementation will make the difference between success and failure – from management sponsors to project manager to subject matter experts.
  3. Know your Industry Requirements – There are multiple levels of manufacturing processes with different levels of requirements, making it critical to keep the requirements of your specific industry in mind. Many MES solutions have been designed for continuous or batch manufacturing environments so when you are researching for an MES provider, you want to find solutions that are focused on complex, discrete manufacturing.

2) MES Solution Design

The design (engineering) phase is following the advise phase and is prior to the development phase. Engineering a MES system can be a complex job because it affects several business processes. The first step after a software solution is selected and user requirements are clear is to translate the user requirements into a functional design. The technical design engineering will describe in detail how the software is structured and the hardware is technically setup.

3) Integration Design

MES-PLM-ERP integration is crucial to the notion of a digital enterprise, where the real-world environment – from concept design to physical production of a product through customer usage in the field – is connected and simulated in a virtual world. By weaving a digital thread throughout all phases of a product’s lifecycle and by connecting core systems, manufacturers can gain insights to help optimize the product and key processes ro achieve higher levels of productivity.

MES Technical Track

1) MES Modeling & Configuration:

The incremental nature of the modeling approach facilitates continuous improvement of the plant process. The elements of the resulting model are used directly in the configuration of object oriented MES systems.

2) MES Customization

MES UI MES UI requires good UI customization, flexible reporting and ease of access.

3) MES Integration

Manufacturing execution system (MES) software helps manufacturers to smoothly manage daily processes. MES integration with other systems – including ERP and SCM – makes this even easier. The integration of MES with ERP systems enables manufacturers to orchestrate work orders and other resource needs. Integrating real-time data about the availability of materials across the entire supply chain with ERP systems can help manufacturers minimize unnecessary interruptions and delays.


Manufacturing Intelligence

1) Static Reporting

Detailed production reporting with static reports and live dashboards. Static reporting gathers real time data from your equipment to give you a solid overview of your production. Systems generate standard production reports that can be broken down by time, material, customer, and other parameters used for internal and external reporting needs.

2) Dashboards

Manufacturing Intelligence software is embedded in your manufacturing system of record and includes specialized database structures, naming conventions, reporting and dashboards pre-built to provide the insights a manufacturer needs to manage the business and support continuous improvement.

3) Data Analytics

As manufacturing moves towards Industry 4.0, software and big data are the main drivers in the sector’s transformation. Big data refers to datasets whose size is beyond the ability of typical database software tools to capture, store, manage, and analyze effectively. By introducing software-based big data analytics and more flexible production techniques, manufacturers can boost productivity by up to 30%.

4) Predictive Analysis

Business Intelligence is needed to know what has happened in the past, but you also need predictive analytics to optimize your resources to make better decisions and take actions for the future.