299. Design procedure to develop dashboards aimed at improving the performance of productive equipment and processes
University of Minho, Portugal
Technological evolution and constant changes in customers’ and other stakeholders’ requirements challenge the organizations to keep up with those changes and at the same time maintain high levels of quality. Considering those requirements, the kaizen approach, more specifically the TPM methodology and its pillar kobetsu kaizen, and the visual management, are key elements to ensure organizations’ response to this challenge. The dashboard is a potential visual management tool that presents key information in order to achieve the objectives defined by organizations. In this way it allows the users to identify, explore and communicate problematic areas that need intervention and to improve decision making.
Even though we find in the literature information about the implementation of dashboards in companies, there is visibly a gap concerning methodologies to develop dashboards oriented to continuous improvement at the shop floor level. This paper intended to fill this gap, having as main objective the development of a performance improvement support methodology to the processes and production equipment, based on the development and implementation of a dashboard.
The work was developed in the context of a pilot company, with the involvement of the employees associated with the production areas. The development of the methodology was based on: the diagnosis of the pilot company; requirements survey; development of a dashboard model and the computer system to support its deployment; development and implementation of procedures and resources needed for the implementation. As a result, it was found that the steps followed were effective against the support methodology objectives. So, a generalization of the developed methodology was realized in order to be a guidance to other companies that want to improve the performance of their processes and productive equipment.
The paper provides useful information regarding the application of dashboards on operational level to improve performance management and decision making. It also explores the challenges in implementing this visual management tool from a practical perspective.
366. A generic decision support tool to planning and assignment problems: Industrial application & Industry 4.0
1ENSAM, France; 2CEMUC, Department of Mechanical Engineering, University of Coimbra, Rua Luís Reis Santos, 3030-788, Coimbra, Portugal
Decision support tools are essential to help the management of industrial systems at different levels: strategic to size the system; tactical to plan activities or assign resources; operational to schedule activities. We present a generic and modular decision support tool to solve different problems of planning, assignment, scheduling or lot-sizing. Our tool uses a hybridization between a metaheuristic and a list algorithm. The specification of the considered problem is built into the algorithm list. Several tactical and operational problems have been solved with our tool: a problem of planning activities with resources assignment for hospital systems, a lot-sizing and scheduling problem taking into account the setup time for plastic injection. The scheduling problem with precedence constraints is being solved. At the strategic level, this tool can also be used as part of the Industry 4.0 to design reconfigurable production systems. This paper summarizes the already solved problems with the proposed tool, and presents the
evolution of our tool.
288. Engineering Change Management Data analysis from the perspective of Information Quality
Tampere University of Technology, Finland
Advanced manufacturing companies process a large number of Engineering Change Requests (ECRs) every year. Having a steady flow of ECRs and an efficient change management process is vital to companies in order to continuously improve their products from perspectives of different stakeholders. The processing times for ECRs vary, among other factors, due to quality of the requests. While a small number of requests gets processed in less than a day, for some the processing may take up to one year. The long processing times lead to unnecessary delays to the requested improvements that would, for example, bring added value to customers or decrease manufacturing costs of products.
This paper is based on the thorough analysis of two thousand Engineering Change Objects and a number of semi-structured interviews conducted in a case company. The case company has sales, engineering, manufacturing and service operations that are globally distributed in different sites and offices. The company processes more than a thousand ECRs yearly, and the number has been increasing significantly during the last decade. The goal of the research was to find out reasons for the varying ECR processing times by classifying Engineering Change Objects and by searching for similarities, differences and reoccurring patterns within the ECR data.
The analyses show that while it is possible to find patterns and create guidelines related to information quality, in many cases analyzing data afterwards is difficult due to part of the Engineering Change modification history disappearing during the process. The final form of a change request is usually of an adequate quality to the handler, even if the initial request was missing several key elements. However, while the primary handler of the ECR often needs only a certain amount of information, ECRs should include more than the minimum in order to be comprehended also by other stakeholders who use the data. Also, it is not enough that the ECR is comprehensible to current handlers; it also needs to remain usable in the future.
267. Proposal for the representation of mechanical and motion control schematics, MMCS
Vigo University, Spain
Manufacturing machines design is a process that combines knowledge of different areas. Many modern machines use motion control systems –inverters, servo-drives, synchronous motors, encoders, etc.-, and the interaction and interdependence between mechanics and electronic control is very high. In modern machinery this complexity increases with the possibility of defining temporal and electronic kinematic relations between axes–as for instance master-slave relationships, CAM table dependencies, etc.–, as well as the use of virtual axes associated with real axes for control reasons.
During the machine conceptual and detailed design, the mechanical elements and components representation come naturally, but not so their relationship with control devices which drive them. On the other hand, control programs and algorithms uses very simplistic representations of the mechanics; just as black boxes. Mechanics, electronics and control have their own widely used standards and design methodologies. However, they are oriented to their particular scopes, and hence to their elements and relations representation strategies. They hardly provide the possibility of providing or including relevant information from another field.
A review of the different standards used in graphic engineering from the mechanical and the control field (ISO128, Technical Drawings, ISO 3952-1: 1981 Kinematic diagrams - Graphical symbols, ISO 369: 2009, PLC-Open for motion, IEC 61131, STEP UMRM, etc.) brings the conclusion that there is no adequate representation methodology to cover, for the new modern machines requirements, mechanical and control design views at the same time. This article develops a new designing information model for this situation. This new systems representation method is a combination of the main standards used in the design of machinery, but taking into account only those common and relevant information for all technology views-mechanical and control- obviating what would be considered irrelevant for the rest.
This new model, in its digital representation, can help achieve some of the objectives of an industry 4.0 implementation: “a model of the ‘smart’ factory of the future where computer-driven systems monitor physical processes, create a virtual copy of the physical world and make decentralized decisions based on self-organization mechanisms”(1). Or more specifically, this virtualization is defined as a virtual copy of the Smart Factory created by linking sensor data with virtual plant models and simulation models (2).
The model presented in this paper will be worth for the design process of complex machines. The use a “graphic” version of the model would bring profits in the communication and understanding between mechanical designers and control designers. And an “digital” information model would become in the link between the "software model" and the "mechanical model" of the virtualized machine/factory.
The article presents the foundations of this new modeling information system and methodology and some case use examples.
 Ron Davies. Industry 4.0: Digitalisation for productivity and growth. EPRS | European Parliamentary Research Service.
 European Parlament. Directorate general for internal policies. Policy department: Economic and scientific Policy. Industry 4.0, 2016 (ISBN: 978-92-823-8815-0).