Reading this could give the impression that everything was right with the world. Undoubtedly, Germany still occupies a good starting position that is worth defending. However, similar to the automotive industry, the plant and mechanical engineering sector faces structural change and multiple challenges:
- a global economic slowdown, trade disputes and a lack of demand from traditional markets are causing sideways movement in familiar territory, with some even talking of a looming recession.
- Companies are seeking growth in previously unknown markets where they are confronted with changing market requirements and huge uncertainties with regard to their products.
- In particular, there are hopes that additional growth stimuli and profits can be found in the expansion and diversification of product and service portfolios in the context of new technologies and digital business models (IoT, climate, CO2, electrification, service ondemand, pay-per-use, etc.).
- Value chains are being rethought, e.g. cooperation in agile, adaptive networks with horizontal and/or vertical integration: skill synergies and significant reductions in lead times, while simultaneously achieving a high adherence to delivery dates, are the objectives.
- The human is still the most important source of inspiration and ideas but, at the same time, also an impediment to growth. Reasons for this include a lack of new required skills, qualified young talent and specialists within companies.
On the meta level, these challenges have now been recognised at management levels and generally acknowledged. Furthermore, the growing significance of the digitisation of products, services (sales growth), processes and structures (increased effectiveness and efficiency) for sustainable business success is beyond dispute.
In our view, the long-term success of a company is a matter of possessing precisely those capabilities that are in demand at a given time. This means developing the right structures and framework conditions within the company that enable an organisation to rapidly and nimbly adapt to changing market conditions (customer requirements and volatility). Thinking through scenarios ahead of time and an agile, targeted, consistent implementation make all the difference here.
So far so good. Specifically, however, this means finding comprehensible, workable and cost-effective solutions in individual cases for the company concerned. As a result, many plant and mechanical engineering companies are now focussing on data-driven business models (rental and operator models, monetisation of production data, new services, smart maintenance, etc.). Ultimately, this is nothing new. These ideas have been around for a long time. However, unlike in the past, the technical prerequisites in the context of Industry 4.0, the Internet of Things, big data, artificial intelligence, augmented reality, cryptography, etc., have now attained a marketable level. But how can companies exploit the plethora of technologies, data and potentials in a competitive and profitable manner to increase the value of their business?
The observations above make it clear that successful implementation does not come at zero cost. It is also evident that the original machine or plant is no longer the focus of considerations. Everything becomes digital - in short: the products should somehow become speaking and be able to communicate with their surroundings. This requires a robust plan and targeted investments in the future. At the same time, it will be necessary to maintain the financial flexibility of the company and reduce production costs (in-house production and external procurement) within the existing product portfolio to the greatest possible extent, while still living up to the brand promise. Companies need to be operationally excellent, or rather LEAN².
In plant and mechanical engineering, two business processes are critical to the success of product creation. Firstly, the interdisciplinary and cross-functional product creation process and, secondly, the agile order processing process with separate process, supply and assembly chains. Nevertheless, the procedural borders are becoming increasingly fluid. In this context, important keywords are the digital twin or, pared-down, the digital shadow of a cyber-physical product in a networked and adaptive development and production environment. However, in order for the product and value added units to be intelligent, networked and adaptive, a multi-layer, comprehensive communication model is required: distributed sensor and actuator services, open programmable logic controllers, and an intelligent production control system that is closely linked to the ERP company level and overlooks cloud-based interfaces that are open to customers. Ideally, these are all seamlessly networked with each other or maybe even directly constitute a holistic data platform that can replace numerous long-serving systems.
To clarify matters, lets take the example of a machine tool: using machine learning, the digital image of a part to be produced on a machine with particular process parameters can contribute to an improvement in quality predictions and thus reduce scrap rates. Furthermore, an intelligent workpiece can contain its actual geometries and machining sequences, which can lead to optimised process parameters during subsequent processing or optimised product pairings. The part to be produced knows its history and its current status in the value chain at all times. The traceability of valuable products at the individual parts level is therefore merely a windfall gain. Moreover, the machine tool used can already provide constant information about its wear condition and, if necessary, autonomously trigger a planned tool change. The machine proactively informs the customer service of upcoming service activities and arranges the date, independently coordinates spare parts requirements and measure according to the current utilisation and need, without the intervention of a third party. The classic service organisation turns into a highly developed network of experts, and a spare parts inventory at the customer’s premises seems like something from an old film. These examples are far from exhaustive.
Initially, the idea of horizontal and vertical networking seems very charming and fires the imagination, but there are many unresolved questions to answer: How is this technical feasible? What risks are involved for business success? How does the unadulterated economic viability look in a concrete cost-benefit analysis? Is the expenditure for data preparation and processing worthwhile when products are becoming increasingly short-lived? What data should a digital shadow or an intelligent product contain, and what added value will this ultimately bring for customers and the company? Or will we just create more difficult-to-maintain data cemeteries? How will using artificial intelligence benefit me in the production of tomorrow? Lastly, the question remains as to how a benefit or added value is to be quantified and what a sensible path for the transformation looks like.
Notwithstanding some hypotheses to the contrary, all this will not be accomplished without humans and effective organisation. A high degree of adaptability, i.e. agility is important. With regard to humans, this means agile development teams and agile mini-factories in hybrid forms of organisation. The human is and remains the most flexible controller in an environment of increasing complexity. As things stand today, the “artificial intelligence” is still embodied by the human in front of the computer. In fact, the task is to ensure the flat and effective networking of the right minds, digital aids and the necessary skills across organisation, and even company, boundaries. More than ever, today's business environment requires collaboration in networks and the ability to adapt quickly. Digitisation is the enabler here. The right forms of operational and organisational structures and resource allocation in important regions and markets essentially depends on the culture and maturity of a company. There is no contradiction between core business of a highly repetitive nature and agile units in uncharted territory. It is important to reduce organisational complexity to the minimum necessary: advance standardisation wherever it makes sense; allow for individuality and agility wherever it is necessary. Ultimately, irrespective of the current economic situation, a definition of roles, tasks and responsibilities jointly supported by managers and employees is required. Continuous learning is an important element of corporate culture. When, in order to remain competitive in the market in the medium term, the need for a change is recognised within a company, some questions are frequently asked: How do we create a suitable macro-organisation? What agile or hybrid elements enable us to respond more flexibly to the market? Flat hierarchies and lateral management: how? Swarm intelligence from us: how? What are the future key and core competences? How do we meet the necessary demand for resources and human capital?
At INNOand, we rely on the proven triad of innovation, organisation and transformation. We will happily be your partner and, together with you, we will develop an individual solution adapted to your current situation.