Manufacturing Execution System (MES)
Assembly Line
What is MES? Key Features You Need to Know!
Price Industries casts eyes on four-year, AI-enabled partnership
Price has now teamed up with a pair of Manitoba companies to design an artificial intelligence-enabled manufacturing execution system (MES) that will take advantage of efficiency technologies that do not currently exist in the market today.
Along with Mode40 (a manufacturing software design shop out of Steinbach) and Innovair (a Winnipeg distributor of robotics equipment for the manufacturing industry), Price is working on the project partially funded by NGen, the country’s advanced manufacturing supercluster. Called “Discrete Manufacturing Assembly Transformation,” the four-year project is expected to be transformational for Price.
China Mobile, Haier & Huawei Digitalize Production Material Management
IFS Cloud for Manufacturing: Unlocking the Power of AI for Intelligent Automation
The IFS Cloud for Manufacturing uses AI technologies to drive Manufacturing Execution Systems (MES) and Manufacturing Scheduling & Optimization, ultimately enhancing the efficiency and agility of manufacturing operations.
Smart manufacturing for personalised medicine
An experimental personalised cancer vaccine from Moderna has shown effectiveness against melanoma when combined with Merck & Co Keytruda immunotherapy, cutting the risk of recurrence or death by 44 per cent compared to immunotherapy alone. The vaccine uses mRNA sequences tailored to the unique mutational signature of each patient’s tumours to stimulate the production of neoantigens and elicit an adaptive immune response. Though this type of treatment shows significant promise, manufacturing and scaling up production of personalised medicine like this will be a challenging process.
The unique demands that personalised medicine will bring will require smarter, more advanced methods. Automation and smart software platforms such as manufacturing execution systems (MES) are becoming more commonplace in pharmaceutical manufacturing and will undoubtedly be essential in this new generation of therapeutics.
Examining Composability: What Should it Look Like in Real Life?
The dynamic nature of manufacturing operations necessitates a dynamic set of interactions between the four key personas in composable business. As we mentioned in the beginning of this post, in order to successfully implement the “anything is composable” mentality, developers need to be everywhere. A framework for success like the one described here can make that a reality for manufacturers of all types.
AQL in Medical Device Manufacturing and the role of MES in its implementation
AQL Defined: ISO 2859-1 establishes AQL (Acceptance Quality Limit), as a sampling-based method for determining quality through inspection of attributes. In simpler terms, AQL is the maximum number of defects allowed in a given lot above which the entire lot would be rejected, or the lowest level of acceptable quality.
An MES application, configured for the medical device industry, allows for the creation of sampling plans, based on risk and for those plans to be enforced either on a time or counter basis. The application supports AQL and allows the definition of measurement tools, along with their calibration status and switches severity automatically which is an advantage for high mix production facilities. It measures both variable and attribute data points based either on time or counter and can be integrated with material logistics to give users a complete view of the quality as materials move across the production line and are converted into the end product.
This month cover story of @TMDmag features our case study from @ultradent.
— Critical Manufacturing (@CriticalMfg) March 14, 2022
Read the story to learn how this global dental manufacturing company is taking big steps towards the future of manufacturing.https://t.co/u5IUiXQJMH
Make the Most of MES
MES software is by no means a new tool for manufacturing, having been around since the mid-1980s. However, for various reasons, manufacturers of all sizes in all industries often don’t take full advantage of the software’s capabilities. New benefits like scalability, affordability, low-code programming and traceability, complement traditional ones like error-proofing and optimizing workflow.
Miklosey says some end-users increasingly prefer using MES systems that prioritize baseline and scalable business intelligence (BI) analysis. These systems let companies access the software’s terabytes of native data with no need for third-party integration. Insights from this data help manufacturers be more responsive to their customers’ needs. FactoryLogix, for example, is readily accessible by the manufacturer’s BI platform of choice.
Meeting the IPC’s Connected Factory Exchange (CFX) standard in MES is another challenge being addressed by software suppliers. Aegis greatly contributed to the development of the CFX, which emphasizes plug-and-play connections to simplify machine-to-machine communication, analogous to USB computer devices.
These Alarming signs show that your Manufacturing ERP or MES is stagnating the business
MES and Manufacturing ERP systems defined the paperless transition of the last two decades. These disruptive technologies were used to collate and aggregate manufacturing data to streamline manufacturing processes. MES solved and still solves crucial challenges such as managing complex data and taking advantage of data analytics.
MES and ERP without AI and extreme automation capabilities means they lack the ability to respond to what really happens on your factory floor and have become one-dimensional legacy solutions in a multi-dimensional context where automating workflows and data-driven insights are essential to cost reduction and profit optimization.
How to calculate digital transformation ROI
To simplify and prioritize the digital vision, first consider how digital transformation for manufacturing integrates three key business components:
- Supervisory control and data acquisition (SCADA), programmable logic controller (PLC) and control (machine automation)
- Manufacturing execution system (MES), which includes: (part traceability, machine monitoring and machine management, i.e., recipes and so on)
- Enterprise resource planning (ERP), which includes: (AP/AR, raw materials, purchase orders, inventory, scheduling and tracking).
Achieving large profitability and competitive gains requires seamless integration of three business components. However, it is important to begin at the machine automation level, then incorporate the MES and finally the ERP. The reason for following this path is based on data requirements but also because it is the easiest path for development.
Big Data Analytics in Electronics Manufacturing: is MES the key to unlocking its true potential?
In a modern SMT fab, every time a stencil is loaded or a squeegee makes a pass, data is generated. Every time a nozzle picks and places a component, data is generated. Every time a camera records a component or board inspection image, data is generated. The abundance of data in the electronics industry is a result of the long-existing and widespread process automation and proliferation of sensors, gauges, meters and cameras, which capture process metrics, equipment data and quality data.
In SMT and electronics the main challenge isn’t the availability of data, rather the ability to look at the data generated from the process as a whole, making sense of data pertaining to each shop floor transaction, then being able to use this data to generate information from a single point of truth instead of disparate unconnected point solutions and use the generated insight to make decisions which ultimately improve process KPIs, OEE, productivity, yield, compliance and quality.
MES & Machine Learning
As the manufacturing sector continues to embrace digitalization, fully integrated manufacturing execution systems will become more and more useful for managing facilities. However, it is expensive for a plant to fully revamp their IT infrastructure. Manufacturers with partially integrated or non-existent MES won’t upgrade unless there are benefits that outweigh the costs, and returns that can be realized.
Incorporating a MES and subsequent machine learning platform into a facility’s or organization’s infrastructure reduces the cost of manual data processing. Tasks that have traditionally taken hours of manual labor, such as aggregating line data to identify trends, can be automated and completed in minutes or less. In this case, machine learning isn’t competing with statistical process control (SPC) or other traditional quality methods; it’s augmenting them so that engineers spend less time to get better insights into their operations.
What is an Additive Manufacturing Execution System?
Additive manufacturing (AM) is the industrial production name for 3D printing. Using computer aided design (CAD) or 3D object scanners, additive manufacturing allows for the creation of three-dimensional objects by depositing materials, usually in layers. As production continues to grow and additive manufacturing industrializes, manufacturers require effective strategies to help them manage their additive manufacturing workflows.
Vaccine production: Marburg has the right stuff
BioNTech manufactures BNT162b2 in collaboration with US pharmaceutical specialist Pfizer. The company has started manufacturing at the production site in Marburg, in the German state of Hesse. The plant there comes with an ultramodern production facility for recombinant proteins. The relevant expertise is also available, since BioNTech also acquired a highly qualified employee base along with the production facility, all of whom are experienced in developing new technologies.
The facility in Marburg had been producing influenza vaccines based on flu cell culture, then changed over to recombinant proteins for cancer treatments and now manufactures mRNA vaccine.
All the improvements at the Marburg plant are Industry 4.0-compatible. One of the challenges with the conversion was the fact that it involved switching from rigid to mobile production with many single-use components. At the same time, working with mRNA meant a higher clean room class than was previously required in the facility. Paper is now an avoidable “contamination factor” that doesn’t arise with digital production. That was the basis for opting for the Opcenter Execution Pharma solution from Siemens as the new MES. This solution enables complete paperless manufacturing and fully electronic batch recording.
Fastems and MTU Aero Engines
As far as possible, system integrators should be experts in the disciplines of both hardware and software. Particularly the “soft” side of automation has become immensely more important, not least because of Industry 4.0. The magnitude of this is demonstrated by a challenging project of MTU Aero Engines AG. The aircraft engine manufacturer was looking for a partner to implement a highly automated blisk production system and opted for Fastems, whose many years of experience in software development enabled it to provide the necessary intelligence for the solution that was envisaged.
According the production manager, the loading and unloading alone means that the Monforts cannot run as autonomously as the milling centers with workpieces requiring long machining times of between 20 and 40 hours. “However, automation with the gantry loader gives us a decisive increase in efficiency. Despite very short processing times of between 20 minutes and two hours, we were able to increase the throughput of these machines by a factor of 4 to 5,” says Walter Sürth, emphasizing the manufacturing quality in connection with the demand for high productivity: “From a technological point of view, the production of blisks is the best that can be expected from a machine tool in terms of precision and therefore repeatability. However, if the workpieces aren’t set up accurately, not even the highest-precision machines are of any use.” This is why the main MLS has three Fastems high-precision set-up stations where the devices can be fitted on zero-point clamping systems for both mill-turning and milling centers. “The accuracy of the set-up stations is comparable to the machine tools. This means potential errors are avoided and cannot even enter production,” says Sürth.
The Manufacturing Management Software (MMS) from Fastems, which is specially adapted to the extremely stringent and specific requirements of blisk production, serves as a nervous system for the overall automation solution. The control system plans the entire production for 96 hours in advance and must constantly be able to manage up to 1,500 jobs. Put another way, this can be around 150,000 manufacturing operations. If the deadline is moved, the MMS reschedules the entire production in real time, again for four days in advance.