The current covid crisis is definitely not the cause for further megatrends in production, but it helps to understand different phenomena that become obvious right now. The situation indicates the robustness and the effects of severe impacts by the market and the general health related restrictions.
Statement 1: The restriction of capital use in production will aggravate. Over the last decades there was often seen a nearly balanced fight between efficiency in terms of cost reduction and a reduction of working capital in terms of capital needed to establish and run a production system. What we see these days is a much higher focus on the reduction of capital use for production systems. Two different aspects serve as an explanation. Firstly, the uncertainty of further business and the volumes that a production system can handle. Secondly, the diversity of the tasks to be performed by a manufacturing equipment. Both leads to the conclusion, that investments need to be payed back earlier and higher production cost per part can be accepted when the total amount of capital needed to run a system can be significantly reduced.
Statement 2: Outsourcing in production will increase significantly compared to today. Following the thoughts of statement 1 it is clear, that investments will focus on the specific core competencies and the core processes of a company in a higher level than today. The lack of capital brings management and shareholders to the point of investigating their `real core competence´ - what they should do frequently and intensively anyway. One of the effects will be determining production tasks (mainly for components and sub systems) as outsourcing potential.
Statement 3: Process technology optimization will become the strongest driver for innovations – across industries. Today most innovations in production processes are the result of a concrete product requirement - classically this is derived from customers’ needs or wants, transferred by a QFD (quality function deployment) into specific production tasks that lead to a shift of process parameter limits and new approaches.
When we presume that there will be much more value adding by production outside of the OEMs, that are responsible for the product, we will detect a completely new way to come to innovations in production processes, far away from the product. Partly we have seen this effect over the last years in terms of big automotive suppliers, where innovation in the processes are not driven by customers. But in the future, there will be a much wider area for innovations without restriction of different industries – only connected by similar production tasks.
Statement 4: The production of components will lose its emotional content. It is not only a romantic phrase but sometimes a result of a long history, that companies produce their own components on a higher cost level compared to somebody else maintaining that task. Of course, there are strategic guidelines behind it and sometimes it is the power of unions and work councils that keep processes inhouse. But the stronger restrictions of capital use and the worldwide crisis will result in a new evaluation with much less emotional aspects as it was before.
Statement 5: The `new pragmatism´ leads to a higher acceptance of new technologies in production. The years 2010 to 2019 have been characterized by a growth in nearly every industry. The company that is able to deliver gets the order. The focus was clearly set on: enlargement of the facilities, availability of people and other resources. In such a time it is hard for new technologies to prevail. Nobody would take the risk of having a slower process with more technical or quality related issues if there is a stable system based on the conventional way. But now, the world has changed into a deep recession, probably having effects on decision for the next 3-8 years. Now it is the time for new ways and for taking risks – caused by the lack of alternatives.
Statement 6: Real innovations in production will be implemented at small and medium sized companies. A trend word of the last years was agility. Coming back to statement 5, where it was written, that the boom years of the last decade are over, agility gets a completely new meaning. Now it is really necessary to become agile, not for a better result but for surviving. The Greek word “skepsis” which in most languages has a negative connotation of rejection regains its real meaning of evaluating on neutral criteria and this will play a relevant role for the future, when decisions have to be made. Of course, such a paradigm shift will be much easier handled by small and medium sized companies due to simple hierarchies and a more likely match of responsibility and know how in one person as it is seen in bigger group of companies.
Statement 7: Collaborative robots will play a starring role in the industrial world of the next 5 years. As it was written before, the trend to more big investments for long lasting production series for one configurated product will collapse. But this will not describe the end of automation. On the contrary, more robots will be implemented in the production of the future as we have seen today. A lot of studies indicate a much higher volume of robots in productions all over the word. But it will be crucial to understand which kind of robots this will be. Taking into account that there is a much higher focus on the flexibility and the capital saving for manufacturing companies, the approach of collaborative robots (hand in hand working of robots and human beings without a fence in between) will fill this new gap of requirements to save money in production and get the maximum flexibility on further applications of such an investment.
Statement 8: The increasing usage of collaborative robots will indicate the digitalization change in production. The technology of collaborative robots has been improved over the last 10 years and besides the better assurance of safety and the increase of potential applications in handling, testing, assembling parts and managing tools, this technology is now on an affordable level. For a lot of companies, the implementation of a collaborative robot is the first step into automation of their processes. Clever and flexibly systems show use cases that can be implemented within a few days and turn into a cashback within a short time. But, even if it is a “new colleague” for the people in production and sometimes a welcome support, it is a device equipped with sensors and actuators, potentially sharing signals and giving the opportunity to have a fully transparent production process.
Statement 9: The first step of a fully digitalized world in production is a real time signal recording of all direct and indirect processes. Fully automated production areas already share their KPIs with systems to analyze and consolidate data for monitoring purposes and improvement detection. Since the production scenario is described by much more than only automated production cells, the activities today maintained by people in assembly lines and production managing processes are mainly not digitalized. The implementation of new tools and devices, e.g. collaborative robots allow the closing of the gaps that interrupt the digital chain today.
Statement 10: After the collection of all relevant data and parameters the next step will be the establishment of optimization algorithms. Today there is no relevant production area in industry working on AI based optimization algorithms.
Nevertheless, the logic behind it, which could be based on balance scorecards, top down KPIs and their specific targets, is state of the art in production management, nowadays given by the management and adjusted.
Statement 11: Artificial Intelligence will take over the formulation of optimization algorithms in production. Depending on the complexity of influences and the capability of describing the logical interdependencies more and more computer based algorithms will formulate optimized set of input parameters. What we see today within different single process steps, e.g. high pressure internal forming of tubes, what is only efficient with a clear detection of response caused by process input forces, will be standard for complex process chains in future. Also approaches of machine learning, e.g. at complex flattening processes after heat treatment of metals will be established for process chains, entire plants or even complete manufacturing companies.
Statement 12: The time will come, when machines will replace human beings as decision makers for production tasks. After AI will formulate optimization algorithms and it can be seen that there is a certain robustness regarding the results tested in diverse situations and scenarios, it is a question of time to change the roles. Perhaps it will happen first in a small production cell, where clear targets of resource inputs and part outputs are given. It will be up to a computer based and ongoingly changing algorithm to find all answers that are necessary to fulfill the production management requirements.
Statement 13: The role of people in production will change into operators when automated devices are not able to execute special tasks in an efficient way. The limits of automation can be seen in many production plants today. For example, handling of parts, visual checks, picking, sorting and complex assembly steps sometimes cannot be automated properly. One example is the wiring harness assembly in almost every industry. Combined with the investment of plants in low cost regions the manual solution of this process is by far the most economical solution for this production task. Also for the future, there will be processes that are not feasible to be automated.
Statement 14: A worldwide high performance production makes only sense, if a high demand can be ensured. A careful hypothesis: The work of 0.5 to 1.5 billion people could be replaced by robots or other automation devices within the next 20 years – from the technological view. Assuming, that these people partly (about 10-20%) will be needed in higher qualified jobs to maintain the technical systems and for planning and management purposes, one could say, that the production performance related to cost and output could be doubled – but it has to be ensured that there is a market for the resulting products out of these high performance production plants. However, what if a number of 1 billion people are not needed anymore as workforce. The poverty will increase and the economical effects will lead to lower market volumes. This example is highly simplified, but it shows a kind of a philosophical dilemma that has to be answered far away from any production technology perspectives…