New technologies, altered processes, and the restructuring that goes with them, bring challenges to all areas of the business, and present specialist personnel, especially those responsible for quality, with new responsibilities. Whilst there used to be defined standards by which companies oriented themselves, quality management is currently characterised by ever shorter cycles of innovation at the same time as product diversity is increasing. Processes and structures regularly need to be reconciled anew, in order to do justice to increasing levels of flexibility and integration. Nevertheless, especially with the flexibility to self-organise, there are weaknesses when it comes to considering quality requirements. This means that, in the future, it is certainly possible for each manufactured product to have its own path through the production process, which in the event of any problems, will make fault identification and root cause analysis considerably more difficult.
The new requirements of Industry 4.0 force small and medium-sized enterprises, in particular, to focus more on business model innovation. Poor decisions due to the lack of information, or miscalculation of risks and potentials, could result in competitive disadvantages and, in certain circumstances, even endanger a company’s very existence. Already today, and more so in the future, the basis of a successful business model is close-to-real-time data, to generate new services with a clear benefit profile for the customer. Most companies already have large amounts of data at their disposal, which they collect and store but rarely analyse. In a smart factory, the analysis of information from core business processes, such as development, production, sales and quality management, needs to be given a whole new emphasis. This is because only the constant observation and evaluation of each and every process will eventually enable the rapid intervention, function customisation, and early quality planning needed to speed up quality management.
According to the definition in the Gabler Business Dictionary, agility means "... the dexterity, manoeuvrability or mobility of organisations and persons with regards to structures and processes. One reacts flexibly to unexpected events and new requirements. For example, in relation to changes, one is not just reactive but also proactive." What does this mean for quality management?
In dynamic markets and under generally challenging conditions, agility is vital in setting up companies capable of turning a profit. Since classical quality management was created and developed in phases for stable businesses, it no longer meets the demands of today’s agile and continually evolving markets. By implication, this means that a company that wants to survive already needs to know in advance, what the customer is going to ask for tomorrow. Here, preventative quality management plays a particular role, which assumes that quality criteria are already being considered during a product’s development. According to one study, 82 per cent of respondants said that quality within their company’s production was a crucial issue. However, only 48 per cent confirmed that their QM was also a focus during the concept development phase.
This of course has huge implications for quality management. Therefore, if quality managers hold rigidly to classical principles, there is an inevitable loss of quality along the way, and dwindling acceptance by customers and business partners is the logical consequence. Agile quality management (QM) will be the new way.
The fundamentals of ISO 9001 are different to those of agile QM. Classic QM is characterised by customer orientation, management, involvement of people, process-oriented approaches, improvements, fact-based decision-making, and relationship management. The agile concept pursues other aims.
Whilst classical quality management does recognise the significance of the customer, it really only has two actual points of contact with him – when ascertaining requirements and satisfaction – the agile system looks for regular interaction with current and potential customers. Coupled with an iterative approach, which stands in contrast to classical improvement, the customer is actively involved in a product’s idea generation, development and realisation phases. Iteration is highly experimental and can deal very well with failure. It means, always returning to the point where an improvement or a modified solution is possible.
The agile concept also largely does away with the aspect of management within the framework of hierarchies. Therefore, agile organisations follow the principle of self-organisation. Interdisciplinary teams take on roles and tasks, which used to be the province of managers. The competence, communication and complete integration of these teams result in high-speed reaction and very good quality.
Traditionally, the involvement of people meant involving experts with defined competences and powers. In addition, agile quality management also draws upon the knowledge of many. This is enabled by a high level of networking. Agile teams call upon the expertise they need, regardless of function or position within the organigram. Since these activities can rarely be planned ahead, agile QM must stimulate and support this networking.
Even fact-based decision-making is a relic of classic QM, because facts are often missing or they are consciously ignored, in order to achieve a desired and apparently scientific result. Of course, facts are necessary for finding solutions, however the agile concept sees more chances for success if the crux of the matter is identified, from which a promising solution may emerge.
The stated aim is to rearrange organisations in such a way as to make them able to perform and survive within the new working environment. This of course also impacts quality management and quality assurance. In particular, these can and must make use of new technologies.
The increasing number of agile organisations and organisational areas need agile quality management in the form of automation, utilisation of smart data, simulation, and networking throughout the supply chain.
In the context of automation, for example, real-time recording can take place in manufacturing processes, using modern sensor and measurement technologies. They detect the slightest variations and emerging difficulties in the shortest possible time and quickly deliver concise information to the relevant specialist departments.
In support, simulations can be carried out before the start of actual production, to avoid expensive trials with real materials, or also to identify sources and causes of errors ahead of time. Virtual quality assurance enables observation of customers using products that do not yet exist, and so provides insights into customer requirements. Furthermore, future product features and the inclusion of special components in systems can be tested in advance, which in turn provides information for design and manufacturing processes. In this way, countless product variations can be tested, and it will be possible to do without initial physical samples, which will speed up the whole process.
The complete networking of all supply chains is the stated goal of Industry 4.0. Thanks to comprehensive communications among all those involved in the process, this enables a flow of information that serves development, quality assurance, logistics and production control in the best possible way. The synergies that result should be promising. At this point, however, there are still some legal questions, such as the protection of intellectual property and who owns which data. There is also a question mark over who coordinates all of these processes?
With absolute certainty, answers to these questions will be found. New business models and innovative solutions will arise. The important thing is, that companies are already preparing for these developments, making rigid processes more agile, and quality managers are adapting themselves to the new requirements. Our experts at ARTS will be delighted to support you in further developing your quality management and in preparing for Industry 4.0.