A Method to Distinguish Potential Workplaces for Human-Robot Collaboration

摘要

The high dynamics of globalized markets and their increase in competition, as well as the demographic changes in western countries causing an increasing shortage of skilled personnel are resulting in major challenges for production companies today. These challenges relate in particular to the processes of assembly forming the last process step in the value chain due to its high share of manual labor. Collaborative assembly, which is characterized by immediate interaction of humans and robots, utilizes the strengths of both partners and is seen as an opportunity to achieve a higher level of flexibility in assembly just as well to support and relieve people of for instance non-ergonomic tasks through automation at work. Although almost every robot manufacturer already has collaborative systems in its product portfolio, these are not yet widely used in industrial production. This might have a variety of reasons, such as the fear of a risky investment or the lack of expertise within the company related to collaborative systems. This article shows a conceptual method that helps companies implementing human-robot-collaboration in their production more quickly and with less implied risk, thus addressing the forthcoming challenges. As a first step, companies must be qualified to make a suitable selection for a possible collaboration scenario. To achieve this, they need a tool to analyze and to evaluate their production processes according to their suitability for human-robot-collaboration. An important feature for an easy and effective use is that the process is formalized so that employees of companies can quickly and easily analyze different processes. The necessary criteria and procedures are developed accordingly and are integrated into the selection method. The main goal is to give the company a recommendation which of their processes are most suitable for human-robot-collaboration, so that they can be used effectively in their production.