Supervised and unsupervised learning in vision-guided robotic bin picking applications for mixed-model assembly

Mixed-model assembly usually involves numerous component variants that require effective materials supply. Here, picking activities are often performed manually, but the prospect of robotics for bin picking has potential to improve quality while reducing man-hour consumption. Robots can make use of vision systems to learn how to perform their tasks. This paper aims to understand the differences in two learning approaches, supervised learning, and unsupervised learning. An experiment containing engineering preparation time (EPT) and recognition quality (RQ) is performed. The findings show an improved RQ but longer EPT with a supervised compared to an unsupervised approach

Future Assembly Information Systems - Redefining the Manufacturing Systems of Tomorrow

Product variety continues to increase as the manufacturing industry introduces customized products and services to address the varying demands of their customers. In the manufacturing industry, it is common for large and global manufacturing companies to grow through mergers and acquisitions. As a consequence, these companies have hard times to find proper information systems integration strategies and to find commonality in their product portfolios. The introduction of Industry 4.0 kick started the digitalization journey that permeates society. Despite the digitalization initiatives, the manufacturing industry has fallen behind in terms of technology introduction in manufacturing systems. In the spirit of Industry 4.0, the manufacturing industry needs practical support on how to prioritize the development of future manufacturing systems. The objective of this thesis is to expand the knowledgebase about the impact of the digitalization in the manufacturing industry. This thesis presents a current state analysis of the challenges of handling assembly information in manual assembly intense manufacturing companies. The thesis also presents critical aspects to overcome the identified challenges and aims to support manufacturing companies in prioritizing initiatives and in making proper preparations for starting the digital transformation. This thesis is based on three case studies conducted between 2016 and 2017. The case studies show that there are many challenges that the manufacturing industry is currently facing that makes it difficult to create smart manufacturing systems. The result of the thesis is intended to be used as input when deploying new assembly information systems to assure high flexibility and operability. Future assembly information systems will allow more customization towards the intended end-user (e.g. operator and engineer), increased automation and data-based decision-making.On basis of the current challenges and the identified critical aspects, an industrial demonstrator has been developed to be used for validation of several design principles that have been formulated. The demonstrator will be tested by real operators during the spring of 2018 and the result will be used to spread knowledge of the impact of enhanced assembly information systems

A state of the art system for managing time data in manual assembly

Valid time data, a prerequisite for the efficient use of manufacturing resources, directly influence planning and control quality. However, access to time data that capture real shop-floor operations in general and manual operations in particular is often assumed by both academics and practitioners. This has led to a mismatch between reality and the data found in systems for production planning and control, causing operational inefficiencies and negatively affecting decision-making in manufacturing companies. This article addresses the importance of updated and valid time data in planning and controlling production and considers how they relate to manufacturing system performance and improvement. The focus is on how to determine, utilise, and sustain valid time data for manual assembly operations through integrating enterprise information systems. The article builds on a case study performed at a large manufacturing enterprise that operates a state of the art system for managing time data in manual assembly. Findings from the case study reveal how standalone system applications can be integrated with the organisational functions of an enterprise to achieve updated and valid operation times