Quality of 4.0 Quality 4.0

Main article the Fourth industrial revolution

Quality 4.0 is an important component of the concept of the Industry 4.0

That forces product companies to pay more attention to quality

To understand what role the quality can play in success of the company, it is not necessary to look further what impact on producers the growing defects and withdrawals of products in terms of financial losses, easing of image and reputation of a brand and also necessary time and resources have that to correct them. Most of producers from among implemented a quality management system (QMS), contrary to emergence of the revocable companies, can solve the arising problems much quicker. However not only defects and responses force to place emphasis on quality. The organizations which use a quality management system cope with the growing requirements of observance of regulating documents, from regulating authorities better.

What is Quality 4.0 (Quality 4.0) and as it is connected with the Industry 4.0

Quality 4.0, less agiotage, than the Industry 4.0, but quickly arising as of 2020, year the concept in the industry 4.0. She tries to classify further those specific technologies, practicians and procedures which allow producers to develop, manage and support the quality standards in all supply chains.

Quality management extends to all processes beginning with development and finishing with shipment of goods to the consumer

The quality 4.0 defines approach which producers can apply at implementation of new technologies. It includes machine learning, predictive analytics, Internet of Things, Big Data and cloud computing - with traditional quality management systems, such as software of a quality management system, - for ensuring continuous improvement and increase in overall performance of business.

Digital technologies which are followed by cleverer practicians and procedures can help to improve quality by different methods. For example, the companies can monitor processes and collect data in real time and also apply analytics to forecasting of problems of quality and the needs for service. Digital instruments also allow people to perform the work quicker, better and with smaller costs.

The quality 4.0 influences not only on what occurs at the plant - it covers all supply chain - from Research and Development before purchases, production, logistics and sales, services and an after-sale service and other corporate functions - up to administration and management.

What crucial elements "Qualities 4.0"

The quality 4.0 covers people, processes and technologies. The first step in any serious conversion - cultural. It requires to consider quality as a strategic business initiative, but not as operational function. For this purpose producers should understand why the quality matters. It is necessary to reveal the painful points and weak points, to attract all interested persons and to set measurable results. The subsequent stages are connected with integration and process optimization for providing seamless flows of processes between different functions and systems. It requires creation of a technology stack and also a quality command to implement these processes. Having created a basis for the successful quality assurance program, the companies can use it for all product lifecycle and an ecosystem of a supply chain strictly to support and exceed the quality standards.

Basic elements "Qualities 4.0"

The main problems on the way to effective management of quality

The research Quality 4.0, Boston Consulting Group (BCG) in partnership with ASQ and Deutsche Gesellschaft für Qualität (DGQ) at the end of 2019, was conducted for the best understanding of a role of technologies in quality management conversion. The main attention in a research was paid to the opportunities, the general calls and technologies connected with quality and also methods of improvement of traditional advanced methods of quality management. According to the report, nearly two thirds of producers consider that Quality 4.0 will significantly influence their work within the next five years. However only 16% say that their company began to implement practicians of Quality 4.0, and 63% did not even reach a planning stage. Though the companies are recognized that Quality 4.0 can create essential value, only the few from them defined detailed strategy and already started the program of implementation. Success with Quality 4.0 can be achieved only using multidimensional approach which - in addition to technology questions - includes also full range the practician. The main problem is the shortage of IT specialists for support of effective programs of quality and the related new technologies. Besides, the quality requires serious change of thinking therefore change management is premises of its success. Pressure upon change of qualitative thinking from top to down can create difficulties. Heads of business should work together with quality managers and IT to support the initiative in scales of all enterprise. Besides, supply chains become harder and harder, and it becomes more difficult to support the quality standards on all way.

What should be effective solution on quality management

The key moment is that the used QMS can be scaled for satisfaction of the changing requirements. It should allow to manage creation, distribution and archiving of all important documents in the centralized and controlled structure. Besides, a system should be rather flexible that it was possible to make use of the best practices, to apply it and to adapt quickly to internal and external business challenges. Besides, such means offer expanded analytics and artificial intelligence which help to make decisions on the basis of data by collecting and the analysis of key figures of merit, such as production efficiency, customer satisfaction or performance of suppliers. However collected data should be easily analyzed and applicable to actions that they could be used for improvement of future results.

Good points from implementation

For the international companies having divisions in the different countries it is possible to implement the concept through the quality assurance program and use of cloud solutions of QMS for automation of the manual document flow, including processes of a supply chain. The automated system of QMS allows to distinguish, define and document the best practices in scales of all enterprise. As a result the company can constantly provide to clients constantly improving products and related services. Time necessary for the supplier for processing of corrective actions was can be is reduced twice, and it means less errors and also it is less than repairs and resendings that makes clients more satisfied.

Overview of the main technologies of the concept Quality 4.0

Predictive analytics of quality

The predictive analytics of quality is the tool used by producers for forecasting of product quality, components and materials which already are in production process.

The predictive analytics begins with cleaning, formatting and the analysis of the huge amounts of data collected in a production process. Then statistical algorithms and machine learning are applied to data to obtain useful information. These ideas are able to allow producers to reveal useful correlations between critical variables, to recognize data patterns, to detect anomalies and to predict future results and trends. It helps to eliminate the root causes of problems in advance - before directly there are any problems with quality. The predictive analytics of quality allows producers to establish abnormal events and basic reasons which can lead to decline in quality of products, influencing products, components and materials.

The concept "Quality 4.0" means implementation of digital technologies in quality management

The research center of electromobility (eLab) at the Aachen university in Germany studied whether it is possible to use predictive analytics of quality for performance improvement by production of accumulator elements. As of 2020 in the sector of electric vehicles the quality of production of accumulator elements is a serious problem - the average percent of defects can reach 15%. It increases the cost of electric vehicles, reduces production volume of accumulators and spends precious raw materials. Costs grow.

The team of researchers of eLab together with specialists in data processing of Elisa Smart Factory started search of the solution for quality improvement of products. The solution was found using predictive analytics. Work began with understanding of production process from the point of view of given by means of a research of data and uses of methods of the analysis of processes (process mining). Then statistical algorithms and machine learning were applied to define data patterns which predicted quality problems further in process.

In a project deliverable of a command could reduce percent of defects of accumulator elements by 16 percent, predicting quality of accumulator elements at early stages of production process.

Machine vision for quality control

In the business lot automated process manual quality check requires big costs and time. So-called sampling inspection, i.e. determination of quality of all production lot by the analysis of a small part of products, because of the growing quality requirements, is not a scalable solution any more. Here join machine vision and deep learning the game that provides factory quality control. These technologies allow to automate control - for each product on the line, with consecutive and exact results of control. Machine vision can exclude a human variable from the equation and provide stable results 24/7.

2D and 3D - control

In 2020 the vast majority of applications of machine vision on production are based on two-dimensional (2D) visualization. It is the fast and safe method of automatic check which offers the analysis for applications, such as reading of a barcode, orientation of labels and check of printing. Three-dimensional (3D) machine vision is most often used for survey and measurement of difficult three-dimensional surfaces of any form. There are several methods of creation of three-dimensional images, including a method of "flight time", a laser triangulation, stereosight, a projection of light bands, "shape from shading" and an interferometry of this world. The most widespread method is the triangulation based on laser scanning using the movement of a product in the course of visualization.

Why visual control of quality requires deep learning

In 2020 it becomes clear that cameras of machine vision are insufficient for quality control on production. It is impossible to identify all defects of quality equally. Actually, determination of how to identify defect on the basis of the image, can be incredibly difficult task. Even the trained professionals can miss fine details, by defects of quality. On the other hand, some signs can mislead the person, risk-averse and force to refuse a product of acceptable quality. Methods of deep learning can be used to teach to detect a quality control system of machine vision different types of defects systematically on the basis of images. Deep learning includes loading in a quality control system of machine vision of thousands of images and its training to learn what quality is acceptable and that is not present, and continuously to improve these results.

Standard Operational Procedures (SOP)

The Standard Operational Procedure (SOP) is a step-by-step set of the instructions describing how to execute routine activity. SOP can be used for providing instructions for accomplishment of the manual and automated tasks and also can serve as the guide to safe methods of carrying out work. Employees should execute their every time equally that transactions remained approved.

Advantages of SOP in production: SOP can help producers to set the approved work methods in the organizations, to support the high level of quality, to ensure efficiency and labor safety, to avoid misunderstanding and to prevent non-compliance with industry regulations. It can optimize production process, minimizing risk of errors. How does good SOP look? The control list of a template of compliance of SOP should be short, simple for understanding and unambiguously formulated. Actions should be lungs for accomplishment. The good standard working procedure should describe accurately steps and inform employees on any security concerns. SOP can provide uniform training for new employees. They also should be updated periodically that they remained relevant for current demands of the organization. How can producers optimize SOP? Modern platforms of corporate content management (ECM) allow producers to implement SOP with expanded functions, such as reliable access control, the centralized control of versions, simple creation and change; and management of procedures.

Programs of role training, workflows and tasks of tasks guarantee that all employees observe the correct procedures, task lists and training. Electronic signatures can be used for confirmation and check of the carried-out tasks. SOP-applications for smartphones do paper printouts, the tables Excel and hand-written signatures outdated now, and general management of SOP by more effective.

SOP can be turned from the simple step-by-step task list into the application for the anticipatory works order using expanded monitoring and process automation. It can cause timely work assignments for the tasks listed in SOP, for example, to order the spare part and to provide the correct SOP for required maintenance.

However the Quality 4.0 is not only technology. It is a new method of quality management. Digital instruments in combination with more advanced practicians and more reasonable processes are able to allow now qualitative commands to constantly provide to clients high-performance products. It can be made when preserving bigger security, more high internal efficiency and also due to ecological and steady transactions.