Sustainability at Its Core

We care about the future of our planet.
As a software provider for manufacturers we know that by developing our MeMOM system based on sustainability principles, we can make a significant contribution to the goals of the transformation to a zero-emission economy. Therefore, our aim is to equip manufacturers with the tools to implement processes that improve the circularity of production with an efficiency-oriented digital transformation, ensuring they are highly eco-efficient.

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Scheduling with priority of waste utilization
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At the core of MeMOM is scheduling. We are able to create schedules for almost all production cases, even the most complex, according to optimization goals selected by the user. To enhance the circularity of production, we have developed the capability to schedule based on the criterion of maximizing the use of waste. MeMOM will identify waste in the inventory that meets the specifications of a given production task and inform the operator of the quantity and location from which it can be retrieved.

Records of waste for re-use
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Approximately 10% of all waste generated in the European Union originates from manufacturing. Some of this waste could be reused if proper records were kept and systems for exchanging or trading waste were established. In MeMOM, shop floor employees can easily report waste quantities and parameters (e.g., weight, length, width, and thickness, dye content, date of manufacture, depending on the type of waste) and receive indications of the location where the waste should be deposited. This process creates a record of the waste, which can be used in the production of other products at the same producer, sold or transferred to other producers (e.g., producers of biogas or natural fertilizers).

Zero-Waste Manufacturing
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One of the primary benefits of implementing MeMOM in a manufacturing company is the ability to detect irregularities in production processes in near real time. These can include quality defects in products. By detecting such irregularities at an earlier stage, companies can avoid wasting resources and take effective corrective action without negatively impacting their order margins. MeMOM enables the automation of quality control processes through digital reporting by operators on the production floor, allowing for the identification and implementation of remedial steps (machine calibration, change of raw material, demagnetization of granules, etc.) in a timely manner. As part of zero-waste production, manufacturers are also utilizing mechanisms to record and reuse waste.

MeMOM software - screen from app presenting Gantt chart in context of machines
MeMOM software - screen presenting calculation of eco -efficiency in application
Monitoring resource consumption
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MeMOM enables the real-time tracking of all resources consumed in the production of a product, from raw materials to recycled materials, utility consumption, and packaging. Consumption data can be sourced from sensors, other systems, or entered manually at a terminal located on the production floor. The data is available in real time, allowing for immediate reaction in the event of high energy consumption relative to target levels. This will enable you to identify any issues at an early stage and to manage resources in a more efficient manner. Once the production process is complete, you can analyse the resource consumption reports to identify any inefficiencies and implement corrective measures.

Measuring Eco-Efficiency, Carbon Footprint and Life Cycle Assessment
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MeMOM is a valuable tool for calculating sustainability indicators, including production eco-efficiency indicators. These indicators measure the benefits of a product in units specific to the product, such as weight, number of pieces, or its value relative to a measure of environmental impact. Examples of these measures include GWP (Global Warming Potential), CO2 equivalent over a specified period of time, and LCA (Life Cycle Assessment), which is the environmental impact of a product over its lifetime. The collection of actual production data allows us to create a record of resources consumed for each product, which can be assigned various measures (e.g., CO2 emissions, N2O). This process significantly automates the calculation of these indicators.

Improving energy efficiency
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In Europe, less than 20% of energy is still derived from renewable sources. This underscores the need to prioritize energy efficiency in production processes. MeMOM offers a solution through integration with sensors, enabling the measurement of electricity and gas consumption by individual machines for specific products. Additionally, schedules can be optimized to minimize utility consumption. Prioritization can be given to machines with lower energy consumption in the production of a given product. Furthermore, scheduling can be adapted to scenarios of variable tariffs or those related to variable availability of renewable energy sources.

Cloud computing
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Data centers are a significant source of greenhouse gas emissions in the IT sector, and optimizing them can contribute to significant reductions. The operation of the MeMOM platform, which can process large data sets at a time, requires considerable computing power. If every customer were to purchase servers to meet these requirements, MeMOM would generate a sizable carbon footprint. Because MeMOM is a cloud application, our customers can take advantage of shared resources and reduce their carbon footprint. Larger computing capacity is required on an as-needed basis for each customer at a different point in time, which optimizes data center utilization. At the same time, our customers' data remains closely guarded and the security of such a solution, thanks to the support of the world's largest cloud providers, is superior to traditional solutions.

Extending the life of the machines
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The MeMOM application offers the ability to monitor process parameters in real time, such as energy consumption or process temperature, using sensors. Additionally, it can retrieve data directly from machine controllers. The analysis of such data sets performed within our platform and the capture of deviations from a defined norm support the prediction of failures and required maintenance work, thereby extending machine life and reducing the carbon footprint and the need to spend money on new machines or costly repairs.

Screen presenting Kubernetess dashboard