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Production software
System QMS (Quality Management System) is software that allows you to improve production processes and detect errors before they become complaints. Thanks to quality control, the production line can meet the expectations of the most demanding customers. It is also a path to maintaining the highest certification standards, as well as legal and regulatory obligations.
The system should provide functionalities enabling quality management in three main areas:
Quality control is one of the basic methods of eliminating errors and production problems, as well as delivering products that meet specific standards and quality requirements. Data collected during the quality control stage, regardless of whether manually or automatically, can be used for further analysis, hazard detection or improvement of the production process.
Pre-process control primarily includes the verification of all components of the production BOM, i.e. raw materials and components used at further production stages. Detecting a defective batch of components or raw materials allows you to avoid costly mistakes that often cannot be repaired at further stages in the so-called rework.
Inspection of semi-finished products between production processes allows not only to detect irregularities in previous production processes, but also to indicate readiness for the next stages of production. If, for example, inter-process seasoning is involved, we can use samples to check whether a given batch is already or still suitable for the next production stage.
Defects and problems detected at this stage can often be repaired by sending the product or batch again to a given production stage or to a dedicated repair station. Inspections may apply to all items, but may also be random or even result from automatic suggestions regarding specific combinations of items from the BOM.
The final control is verification of the correctness of production in relation to pre-production documentation and the order. It also involves checking packaged, ready-to-ship batches and their specifications in relation to the delivery schedule to customers. At this stage, products can be classified for certification and may be provided with quality documents.
Cause-and-effect analysis is one of the most effective risk management methods. In the lean manufacturing concept, using e.g. the Ishikawa diagram (fishbone diagram) allows us to identify quality problems that affect our production. Regardless of what methodology we use, it is worth paying attention to two aspects: firstly, according to the Pareto principle, 80% of problems arise from 20% of the causes, and secondly, to detect the causes, data must be recorded.
Recording detailed production data allows you to build multidimensional reports. This data is a key value in the further improvement and risk management process because it allows you to detect patterns and patterns.
Conducting the analysis should consist of several stages, taking into account the identification of risk factors in individual processes, their categorization, frequency of occurrence and severity of effects, as well as level assessment. Only a reliable analysis allows you to move to the next stage, which is improvement and prevention.
After conducting a detailed analysis, corrective and preventive actions should be introduced. Thanks to them, the solution to the problem will not be local, but will also help avoid its return in the future. Methodologies related to the management of corrective actions include, among others, corrective and preventive action matrices used, for example, in the CAPA (Corrective Actions Preventive Actions) methodology. Another approach may be to use the FMEA (Failure Mode and Effect Analysis) methodology, also known as FMECA or AMDEC, which also allows you to establish a cause and effect sequence. You can also use continuous, gentle improvement of the production process in accordance with the Kaizen methodology. However, each of these methods needs data and an appropriate place in the system where they will be used and processed.
Responding to local problems requires, above all, efficient interdepartmental communication. The MES module, product traceability or communicator can especially help with this. Withholding products and semi-finished products for inspection allows for additional verification, as well as sending items of questionable quality for reprocessing.
Once we know the causes of the problem, we can modify the process. Regardless of whether it concerns very specific low-volume production or mass production, process improvement should always result in increased quality and production safety. Minor changes to the technology card introduced by operators may be of key importance for technologists who will improve each subsequent process.
Problems should not only be solved but, above all, prevented from occurring. By introducing subsequent warnings and protections against events causing quality problems into the system, we buy the safety and quality of the product, permanently excluding the possibility of defects.
The last element of improvement and broadly understood quality management is continuous monitoring of the OEE (Overall Equipment Effectiveness) indicator. It is a measure of the performance of machines on a production line, which is the product of availability, efficiency and quality. Once you have production data, monitoring this metric becomes trivial and allows you to detect any deviations that may negatively impact the product or production process.
By marking defective raw materials and components, we prevent production that would be burdened with a high risk of quality problems.
Re-accepting the product to the warehouse after returning it from the customer requires special inspection to determine at what stage the defects occurred. It is also possible to repair quality problems or the need to dispose of and repeat the production process.
Reporting quality problems regarding raw materials and components to suppliers makes it possible to register such information and, in the future, allow for additional control of all components from this source.
An internal classifier that allows you to create a ranking of suppliers that most often supply us with defective raw materials and components or those that most often participate in the production processes of products subject to the most common quality problems.
Automatic inclusion of production scrap as an underflow in the production plan. This allows operators to produce the desired amount of the finished product without restarting the production line.
Possibility to block raw materials and components from accidental use in production after they are marked as defective or suspended for inspection.
Possibility to analyze the causes of production downtime, problems and defects registered by operators. Any data aggregation that provides different perspectives to find the causes of problems and preventive actions.
Using machine learning, also known as artificial intelligence (AI), to detect specific production data sets that may indicate a potential problem and inform the need to take remedial action.
A dedicated panel for production operators integrated with MES, thanks to which they can not only report quality problems, but also failures related to the station. Additionally, they can flag production so that operators at subsequent stages are aware of where problems occurred and what they should pay special attention to.
Data preview from MES operator panels is available to all stakeholders - production manager, quality control department, maintenance department and planners. Thanks to this, all departments will respond appropriately to each type of failure, eliminating the causes and building awareness of preventing them in the future.
Good to know
The presented solution is only a demonstration of aveneo's technological capabilities. Our mission is to provide dedicated software (created together with and for our clients) that will be fully adapted and optimized to the operating model and business processes, and not to offer a ready-made, universal product that will require a number of compromises.
Lead time compression - shortened production cycle by minimizing breaks between processes.
Lean warehouse stocks thanks to precise monitoring of delivery dates.
Increased productivity thanks to better inter-process synchronization.
Monitor production progress in real time.
Reducing the volume of work in progress thanks to continuous condition monitoring.
Better internal communication thanks to an internal communicator.
Optimized use of resources thanks to full control of the load on production stations.
Improved timeliness thanks to an organized and realistic production plan.
Flexibility to change customer needs thanks to simple and immediate plan modifications.
Reduce production costs by reducing production downtime and staying on schedule.
Shifted plan horizon thanks to the reliability of planning software.
Planning of multiple stations and production locations without additional work.
Streamline production planning, optimize resource allocation, and ensure on-time delivery with our Advanced Planning and Scheduling (APS) software.
Optimize your warehouse operations and enhance inventory management.
Monitor and control your manufacturing processes in real-time for improved efficiency.
Seamlessly manage energy demand to reduce costs and enhance sustainability.
Trace production in every aspect - from raw materials and components to the finished product.
Enhance customer relationships and improve communication with a dedicated CRM system.
Yes. Manual marking of both raw materials and components, as well as products and semi-finished products in work in progress is the most common situation we address. In theory, the use of the so-called Yellow sticky notes effectively build awareness of which items require inspection, but in practice they do not allow for their quick location and verification. Therefore, we propose integrating items for inspection with both the production panel and the warehouse, so that the quality control department receives immediate notifications about new items along with their exact warehouse location.
Depending on the nature of production processes, we offer digital marking of production defects. The possibilities are almost limitless - from integration with anomaly and defect detection systems, through manual flagging of products, to the use of machine learning (AI) to automatically detect deviations from adopted quality standards.
Of course. Some production defects can be repaired in the so-called rework, i.e. manual repair of the product. Others may require repeating production processes. Still others may be classified as of reduced quality or simply disposed of as unfit for use. When designing a solution, you should take into account product defects that may occur and proceed from them when providing actions that can be implemented in specific positions.
Of course. In combination with other modules (e.g. helpdesk), we can register a complaint and then verify the reported quality problems in the QMS module. Additionally, thanks to product traceability and full warehouse history from the QMSQMS module, we can trace the production process to find the source of the problem. It is also worth noting that the very implementation of quality control with effective software should contribute to reducing the number of complaints and overall improvement of quality, although complaints cannot be avoided.
For this purpose, we use observation of production processes and their components: raw materials and components. Each change in parameters creates a new crossword that is worth qualitatively testing. If a batch of components changes or their new combination is created, new quality problems may arise.
Of course. However, it is worth noting that different methodologies standardize how to deal with quality problems as well as how to avoid such problems. Therefore, it is crucial to consciously choose the methodology (e.g. the mentioned 8D Report) in order to adapt all areas of the software to the characteristics of the process.