In the high-volume food industry, Manufacturing Execution Systems (MES) solutions are often used as a bridge between a digital representative model of the shop floor and the equipment control systems. This piece will explore how different approaches can maximize the combined functionality of MES and ERP integration in the food industry.
MES is defined as a specialist class of production-oriented software that manages, monitors, and synchronizes the execution of real-time physical processes involved in transforming raw materials into intermediate and/or finished goods. The approach and architecture used for integrating MES solutions into the Enterprise Resource Planning (ERP) system for the food industry will have a profound impact on the value and capabilities that the ERP system will be able to effectively provide. Four of the key data elements captured in MES and ERP integrations are Who (Resources), What (Activities), Where (Location), and When (Time). How these elements are captured and at what level makes an enormous difference. This is because a system can only provide information and value from what it knows.
Optimizing MES Integration
In order to optimize the MES to ERP integration, MES may rely on additional integrations, such as equipment control systems, to provide real-time data points that will be fed to ERP for functions like costing and planning. An ERP can receive data from MES – like Start Times and Stop Times – to assess the overall performance of the processes. Manufacturing operations may occur in seconds, and this requires rapidly gathered data that is automatically captured in the MES solution. Additionally, data about key activities – such as the completion of key processing steps, the equipment/labor used, and, finally, the location of the activity – are also logged. There are many examples of equipment control systems that are routinely linked to MES in the food industry which include, but aren’t limited to:
- Scale integration
- Material handling equipment, including conveyors and tube systems
- Preparation equipment, including sterilizers or wash systems
- Automated Food Transformation Processing (Ex. filleting, disassembly)
- Mixing and blending
- Heat processing equipment including ovens and fryers
- Preservation equipment including freezers and dehydrators
- Automated fill operations
- Product distribution equipment, including wrapping and palletizing systems.
Let’s examine some of the current approaches that the food industry is implementing along with some new approaches that complement a more digital supply chain.
MES and ERP Integration Classical View
The classical view of MES integration has been hierarchical and vertical. The International Society of Automation classical ISA95 integration model is shown below. It assumes that each level gets a summary of information from a lower level and operates on different time intervals. However, this architecture with today’s MES and ERP functionality isn’t optimum. Horizonal or Parallel Distributive Integrations, which are embedded into the digital supply chain, are now critical to fully leverage your ERP’s and MES functionality.
Consider ERP capabilities to capture and provide visibility of costs. A simple example is the start and stop time of a blending batch operation, which is required to understand the cost of producing the batch. If the ERP system is only updated on how much is produced for the day, it will not know the cost variance from batch to batch. With the razor-thin margins being common in food processing, true costs will not be understood. Also knowing the resource used (both equipment and labor) can change the product costs. MES integrations can provide this data at a more granular level and in real time to provide more current and valuable data points.
A shift to horizonal integration has occurred as the footprint of the modern ERP system has grown. With the integration of quality, production, distribution, and predictive analytics, the time frames of ERP data capture have moved from days to minute by minute. This is further accelerated with the advent of Industry 4.0 and the incorporation of the Industrial Internet of Things (IIoT) as well as the customer-based Internet of Things (IoT)
The Industrial Internet of Things (IIoT)
Industrial IoT, or the Industrial Internet of Things (IIoT), uses the power of smart machines and real-time predictive analytics to provide insight of high value. IIoT is creating value in the food manufacturing industry with improved food safety being one of the most essential improvements.
Providing real-time temperature data and monitoring production states ensures constant cold chain management for consistent food safety standards. Remotely monitoring food throughout the production process and storage process reduces food waste. Industrial IoT can automatically trigger events impacting quality characteristic values, which can flow to the MES and ERP system. These characteristics are then used to determine usage decisions, product grading and disposition within ERP.
One example would be within seafood – think about capturing a boat’s GPS location data, which can be used to automatically update harvest area characteristics captured within MES and then fed to the ERP, which will in the end be included on the finished products’ labels.
Modern MES and Enterprise Systems Integration Platforms
As the MES and Enterprise Systems architecture has expanded to the Cloud and with the rise of SaaS (Software as a Service) solution offerings, new integration platforms have become available. Leveraging these tools can greatly reduce the effort of connectivity in the distributed systems environment. Some of the benefits of utilizing these platforms include:
- Cloud-based integration platform software will integrate with industry-leading software like SAP, Google Cloud, AWS, Oracle, NetSuite ERP, Salesforce, Workday, Microsoft Dynamics CRM, Shopify, Magento, and many more.
- An integration platform-as-a-service tool that enables faster connections and updating and evolution of data and analytics systems with Internet of Things (IoT) devices.
- SAP data services can integrate, connect, and process structured or unstructured critical data from SAP or third-party sources within Big Data or enterprise solutions deployed on premise or in the cloud.
Edge computing is an approach to reduce risk by avoiding impacting food processing lines and essential manufacturing operations due to intermittent connection to the cloud. Edge computing is performed close to the processing line or warehouse, leveraging more direct connectivity to enterprise business solutions and onsite MES.
Edge computing can provide the following benefits for capturing MES Data.
- Reduced latency: Edge computing processes data closer to the source, reducing the time it takes for data to be transmitted.
- Reliability: Edge computing mitigates the risk of data loss or delays that may occur due to network disruptions by processing data locally.
- Security: Sensitive data can be processed and stored at the edge, reducing the risk of data breaches.
- Scalability: Edge computing allows processing at multiple locations, reducing loading on central servers and making scaling operations easier.
Realizing True Value Creation
Evolving from vertical MES and ERP integration approaches to the horizonal-parallel integration allows for the leveraging of the minute-to-minute batch level visibility within the ERP system. This permits the full realization of the significant integrated capabilities of a modern ERP to be utilized. The result is improved cost visibility, supply chain management, quality, production, and procurement process optimization, as well as enhanced trading partner collaboration. Adoption of this horizontal integration approach that’s embedded into the digital supply chain is the key to unleashing the value creation possible from MES and ERP.