A Framework for Data Integration and Analysis in Radial-Axial Ring Rolling

Data-driven analytical approaches such as machine learning bear great potential for increasing productivity in industrial applications. The primary requirement for using those approaches is data. The challenge is to not only have any kind of data but data which has been transformed into an analytically useful form. Building upon this initial requirement, this paper presents the current state concerning data analysis and data integration in the industrial branch of hot forming, specifically focussing on radial-axial ring rolling. The state of the art is represented by the results of a data survey which was completed by six of Germany’s representing radial-axial ring rolling companies. The survey’s centre of interest focuses on how data is currently stored and analysed and how it gets depicted into eight different statements. Based on the results of the survey a framework is proposed to integrate data of the whole production process of ring rolling (furnace, punch, ring rolling machine, heat treatment and quality inspection) so that data-driven techniques can be applied to reduce form and process errors. The proposed framework takes into account that a generalized standard is hard to set because of already grown structures and a huge variety of analytical methods. Therefore, the framework focuses on data integration issues commonly found in an industrial setting as opposed to controlled research environments. The paper proposes methodologies on how to utilize the potential of each company's data. As a result, the proposed framework creates awareness for saving the data in a standardized and thoughtful manner as well as building a data-driven culture within the company

Method to Automatically Create an Initial Layout for a Production System

A well-proven means to automate processes are industrial robots. Nevertheless, there are still many processes that are not automated, especially in small and medium sized companies. A main reason is a missing automatism to create suitable solutions. To meet this challenge, the ROBOTOP research project tries to find a list of appropriate components and arrange them in a suitable layout. This paper addresses the second step and an algorithm is described that generates a suitable layout. Thereby, a main aim is to generate a layout that is plausible to the user. The problem relates to the facility layout problem and the proposed algorithm is also applicable to non-robotic related tasks. However, current methods do not yield to an appropriate, because due to the simplifications of the used models a manual effort is required when transforming the model to a 3D scene. The algorithms accepts a description of the process and identifies different kind of patterns. For each kind of pattern, layout rules are defined. With this, the model can be transformed to a plausible 3D setup

Methodical Approach for Detailed Planning of Services to offer Product Service Systems

The transformation of current business models towards offering product service systems (PSS) provides manufacturing companies numerous opportunities to consolidate or even expand their competitive position. Companies are confronted with the challenge of successfully designing this transformation process simultaneously. In order to approach the development of new business models and the transformation process, business model patterns and best practices provide a good first orientation for companies. However, these are designed to be industry-neutral and rather abstract when considering the actual processes. Thus, they do not offer any individual support to companies in the specific development of a business model and its required service delivery processes. Service delivery processes are part of a business model and describe activities that take place to provide services. Small and medium-sized enterprises (SMEs) in particular do not have the necessary time, technical and methodological resources to manage a transfer from abstract business model examples to an individual business model. This barrier often leads SME to remain with their traditional business model. Therefore, this paper presents a methodology for the detailed planning of service delivery processes. The designed methodology supports the phases design and implementation, which are part of the business model development. The methodology describes a structured procedure, in which relevant services first have to be identified. These services are then broken down into individual process modules on a second level. The modules are elements that can get combined to services. On a third level there are explicit process models. The process models are assigned to the modules and define the respective process steps and the requirements for the implementation. The approach is designed to support companies successfully transform to new business models for PSS by applying the detailed planning for services with specific modules that contain detailed process models and requirements

Development of a Concept for Real-Time Control of Manual Assembly Systems

In contrast to automated machines and installations, manual assembly still lacks real-time process monitoring and possibilities for short-term control and adaptation of assembly systems. This article describes an approach for a concept of real-time control of manual assembly systems. For this purpose, KPIs that can be determined predictively are considered. These indicators enable a standardized and objective process data acquisition and a local process optimization for a higher flexibility and adaptability. In addition to the key figures developed, an approach for the automated acquisition of appropriate process data in manual assembly is described. The further usage of the KPIs and the validation within a real production environment is finally presented

Cyber Physical Systems for Life Cycle Continuous Technical Documentation of Manufacturing Facilities

AbstractContinuous rising of requirements to create technical documentation results in high effort in terms of time and costs to create a complete and up to date documentation for manufacturers. In case of any technical modifications of machines the technical documentation also has to be updated. In fact these updates are lacking in most cases.In this paper, the authors propose a methodology for a self-organized creation of technical documentation to enable an up to date state throughout the Product Life Cycle. A complete and up to date technical documentation provides benefits to customers as well as suppliers of manufacturing facilities. The new approach is based on integration and communication of all components and modules such as machine tool, transportation and handling technology etc. via “Cyber Physical Systems”

Investigation of Wire Mark Reading Methods to Support Automatic Quality Control

During the assembly of a control cabinet, a worker obstructs many individual configured wires. To distinguish these wires, a printer plots an identifying text on each end of the wires. However, due to the shape of the wires and the printing process, the quality of these markings is often too low, and it is hard or impossible to read the marking. Common reasons are a low contrast or a blurred text. By now, there is no quality check of the marking after a crimping machine produced the wire. This paper investigates methods for wire mark reading that is required to estimate the quality of the marking. By using optical character recognition, the likeliness that a worker can read the marking must be computed. In the final solution, the quality check of the marking will be implemented within an automated quality check that is located after the printing process. With this, the crimping machine can then discard wires of low quality and reproduce them instantly

A systematic literature review of communications standards in discrete manufacturing

Industry 4.0 has a particular emphasis on the data landscape of production facilities. Data is needed to gain essential insights from the production machinery to support operations management in better decision-making or indirectly by feeding decision support systems. Such data is encapsulated in an industrial communication standard to organize in a higher-level ontology. It is challenging for operation technology specialists to have an overview of all those standards because they are numerous. This work contributes a solution to this problem by systematically approaching the literature to give an overview of the industrial communication standards landscape. The method used is a systematic literature review with a backward and forward search consisting of three main phases: 1. keyword-based search on different platforms, 2. abstract screening, and 3. full-text screening. Over 2,100 article abstracts have been parsed systematically to condense it to the most relevant 309 full-text articles. This work presents an overview of the most significant industrial communication standards mentioned in these articles. Several use cases and some brief IT-security-relevant aspects are presented as well

Method For Creating A Control Cabinet Model With Realistic Wires

During the assembly of a control cabinet, a major time-consuming step is the wiring of the included components. Hence, automating this step will noticeably reduce production costs. According to the planning, wires are routed through wire ducts and connected to components. While a comprehensive digital twin can be computed for the included components, this twin is missing a proper modelling of the connecting wires. For these, only a rough route through the wire ducts is given. However, a physically plausible model is an important prerequisite to perform reliable path planning for automated assembly. The paper addresses this need for accurate wire path computation during automated cabinet assembly and introduces a method to compute realistic wire paths through the wire ducts. Different models with and without a fixed wire length are presented and compared. An evolutionary algorithm optimizes the corresponding variables of the models. As described, both approaches yield valid paths, although the fixed length model appears to be able to compute more realistic paths

Complementary database generation for machine learning in quality prediction of cold ring rolling

Reducing scrap products and unnecessary rework has always been a goal of the manufacturing industry. With the increasing data availability and the developments in the field of artificial intelligence (AI) for industrial applications, machine learning (ML) has been applied to radial-axial ring rolling (RARR) to predict product quality [1]. However, the accuracy of these predictions is currently still limited by the quantity and quality of the data [2]. In order to apply supervised learning to predict part quality and possible scrap parts, there must be plenty of datasets logged for both good and scrap parts. One suitable way to increase the number of datasets is to utilize simulation strategies to generate synthetic datasets. However, in the hot ring rolling field, there is no fast simulation method that can be used to generate a sufficiently large synthetic database of rolled parts with form or process errors. The research on transfer learning between different mills and datasets has offered a new idea of taking a cold ring rolling process as the object of study [2]. Next it will investigate the extent to which the cold ring rolling can be used as a similar process for future transfer of models and results to radial-axial ring rolling. Compared to RARR, the cold ring rolling is a process under room temperature and contains complete radial forming instead of simultaneous forming in the radial and axial directions. The simpler forming mechanism makes it possible to build a semi-analytical model, which takes much less time compared to conventional FEMapproaches under acceptable accuracies. Furthermore, the smaller ring geometry, simplified rolling process and reduced energy consumption mean that in-house experiments can be conducted to verify the quality of the synthetic data based on confidence intervals

Improvement of Machine Learning Models for Time Series Forecasting in Radial-Axial Ring Rolling through Transfer Learning

Due to the increasing computing power and corresponding algorithms, the use of machine learning (ML) in production technology has risen sharply in the age of Industry 4.0. Data availability in particular is fundamental at this point and a prerequisite for the successful implementation of a ML application. If the quantity or quality of data is insufficient for a given problem, techniques such as data augmentation, the use of synthetic data and transfer learning of similar data sets can provide a remedy. In this paper, the concept of transfer learning is applied in the field of radial-axial ring rolling (rarr) and implemented using the example of time series prediction of the outer diameter over the process time. Radial-axial ring rolling is a hot forming process and is used for seamless ring production