6. THE FAILURE PRIORITIZATION IN THE AUTOMOTIVE INDUSTRY - THE TWO-STEP FMEA INTEGRATED APPROACH

Banduka Nikola, Tadić Danijela, Komatina Nikola, Aljinović Amanda

Original scientific paper, in the review process in the Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture The Journal of Engineering Manufacture provides a focus for developments in engineering manufacture, covering technological and scientific research, developments and management implementation in manufacturing.

Abstract Traditionally, in the automotive industry, the risk that is induced by the realization of production failures is based on the conventional Process Failure Mode and Effect Analysis (PFMEA). The continuous market changes, as well as scarce financial resources allocated for improvement, make the basis for the emerging advanced risk assessment models. In this research, the rank of failures is obtained by using the proposed fuzzy classification method based on Pareto analysis. It is assumed that the classification criterion should be calculated as product of the overall product preference and RPNs which are given by applying conventional PFMEA. All the uncertainties that exists in the considered problem are described by linguistic expressions which are modelled by the interval type 2 triangular fuzzy numbers (IT2TFNs). The overall product preference is given by using fuzzy Analytic Hierarchy Process (FAHP) with IT2TFNs. The priority of management initiatives when applied, may result in a decreased risk level and at the same time, to the increased business effectiveness, is based on the obtained classification results. The proposed model is tested on real‐life data which came from one automotive company supplier that operates in Western Balkan embracing one entity of the global automotive supply chain. Keywords: automotive industry, the interval type-2 triangular fuzzy numbers, fuzzy AHP, FMEA, new classification method

5. TWO-STAGE PRODUCT DESIGN SELECTION BY USING PROMETHEE AND TAGUCHI METHOD: A CASE STUDY

Marina Crnjac, Amanda Aljinović, Nikola Gjedlum, Marko Mladineo

Original scientific paper, accepted for publication in Curent Content indexed international journal Advances in Production Engineering & Management (APEM) Advances in Production Engineering & Management (APEM journal) covers theoretical and application-oriented research in a wide range of production engineering and production management

Abstract The main goal of this paper was to introduce the methodology for product design selection. The proposed methodology combines two classical methods to find the most appropriate design for the new product, through a reduced number of alternatives (product variants) and experiments for the selection process. In the first stage, the multi-criteria decision-making method, PROMETHEE is used for selecting the most suitable design, according to the chosen preferences and criteria. In the second stage, the Taguchi method is used in order to define the most appropriate parameters for selected suitable design. The fundamental scientific contribution of this paper refers to a benefit introduced by combining these methods. This benefit is related to the reduction of product development time which has a significant effect on manufacturing process time due to the high market pressure. The proposed methodology was applied to find the appropriate table design for CNC milling machine located in the Lean Learning factory. However, this is just one case study to present the proposed methodology which can be applied for other optimization of other product designs. Before applying the proposed methodology for this case study, the methodology is validated on a simple example. Keywords: Learning factory; Lean manufacturing; Design optimization; PROMETHEE method; Taguchi method

4. CONCEPT OF LEARNING FACTORY AT FSRE

Željko Stojkić, Igor Bošnjak

Review article published in conference proceeding and presented on international scientific conference MTSM 2018 The 8th International Conference - Mechanical Technologies and Structural Materials, MTSM 2018, Split, Croatia, 27th-28th September 2018. Industrial progress is closely connected with development and aplication of new structural materials as well as new processing technologies, rational use of existing and developing new energy sources.Particular interest is also concentrated on organization of production processes, quality management and environmental protection.

Abstract Employee’s competencies are the key resources of an enterprise to quickly adapt to ever changing conditions. In this context competency development at all levels is needed for those adaption processes. One promising approach for effective development of competencies is the learning factory concept. In the last years, learning factories as close-to-industry environments for education and research have proven to be an effective concept addressing these challenges. In this paper, the background of term Learning factory will be presented, its different definition that are found in the literature, establishment of the term “learning factory” and its description model. The concept of Learning Factory at Faculty of Mechanical Engineering, Computing and Electrical Engineering, University of Mostar has been presented. Current state has been described regarding, space, equipment and infrastructure. At the end are presented future plans regarding fulfillment the LF concept on FSRE. Keywords: Manufacturing education, Learning factory, Competence development

Full paper available at: http://www.strojarska-tehnologija.hr/

3. APPLICATION OF THE INTEGRATIVE PROCEDURE FOR MANAGEMENT OF PRODUCTION AND SERVICE IMPROVEMENT PROCESS ON THE ASSEMBLY LINE

Nikola Gjeldum, Marko Mladineo, Marina Crnjac, Amanda Aljinović

Original scientific paper published in conference proceeding and presented on international scientific conference DAAAM 2018 29th DAAAM International Symposium, Zadar, Croatia, EU, 24th-27th October 2018. The Symposium includes all topics from the fields of advanced manufacturing, automation, networking, and knowledge. It covers Theory, Practice, and Education of engineers. Focus is on all aspects of design, production, manufacturing, exploiting of all kind of complex technical products made out of more parts, and all aspects of development and use of industrial and service automation.

Abstract Continual improvement of production process consists of small incremental improvements combined with breakthrough improvement steps. These improvements are usually achieved through the improvement of the organization, processes and people skills using improvement concepts like Lean management. Sometimes, usually for breakthrough improvements, significant financial investments in technology are needed. On the other hand, improving of organization, processes and people skills usually do not require significant financial investments.  Therefore, for industrial enterprises, it would be the most valuable to have a procedure for the management of the continual improvement process. The procedure that identifies and focuses on the most important processes or part of processes and selects the improvement action which will have the best effect on key performance indicators (KPIs) of the production process. In this research, an integrative procedure for management of production and service improvement process is experimentally tested on the real assembly line in the Laboratory at FESB, University of Split. The focus of this paper is on the innovative multi-criteria decision making support system for prioritization of proposed improvement processes, based on the HUMANT algorithm. The result is that one proposed improvement process is selected as the most effective solution, according to pre-defined KPIs. Keywords: improvement process, lean management, multi-criteria decision-making, assembly, HUMANT algorithm

Full paper available at: https://daaam.info/29th-proceedings-2018/

2. INDUSTRY 4.0-BASED IMPROVEMENT OF THE LEAN GAME BY USING THE INNOVATIVE DECISION SUPPORT SYSTEM

Nikola Gjeldum, Marko Mladineo, Marina Crnjac, Amanda Aljinović, Željko Stojkić, Igor Bošnjak

Original scientific paper published in conference proceeding and presented on international scientific conference ELEC 2018 5th European Lean Educator Conference (ELEC 2018), 13-17 November 2018 at School of Engineering of University of Minho, Braga, Portugal. The  first  European  Lean  Educator  Conference  took  place  in Stuttgart, September 2014. The second, third and fourth European Lean Educator Conferences were organized in Sweden, England and in the Netherlands with the number of attendees increasing from 100 to over 140 and then to over 200. All  four  conferences distinguished  Lean  as  a  broad  operations  improvement  philosophy  supported  by  a  growing  set  of methods  and  tools.  These  methods  not only include  the  Toyota Production System,  but also philosophies such as agile manufacturing/management, lean-six sigma and quick response manufacturing.  Lean  is  increasingly  used  in  various sectors, such as  manufacturing, product development,  supply  chain  management,  health  care,  education, public  services, offices, and services in general. There are many cross-over learning opportunities between the various fields. ELEC supports this.

Abstract The Lean Learning Factory is used for the education of industry employees and students in the environment similar to the real factory shop floor. The education process has to be adapted to the increasing variability and changeability due to demands for personalized products in practice. By applying a concept of integrative procedure for management of production and service improvement process on the didactic lean game, it is decided which concept will be developed that will assist trainers during a simulation run. The simulation manual data gathering process and the simulation run results presentation require a large effort of the educator. This disadvantage is even more emphasized if slightly different or personalized products is to be assembled in one moment during the simulation run. The main aim of this research is the application of the developed decision support system within a defined procedure for the selection of the optimal improvement variant. It is based on the multi-criteria decision-making with the help of the HUMANT algorithm and Web application user-friendly interface for defining decision-makers preferences. The system is presented and tested. The decision has been presented. It is decided to use an application of Industry 4.0 concept related equipment, RFID readers and tags for real-time data gathering and automated analyzing and preparation of the gathered data for presentation. Keywords: decision support system, improvement process, lean games, data gathering system, I4.0 equipment development, RFID

Full paper available at: http://www.elec2018.pt/

1. TOWARDS EQUIPPING AN ASSEMBLY LINE WITH INDUSTRY 4.0 CONCEPT ELEMENTS IN LABORATORY ENVIRONMENT

Nikola Gjeldum, Marko Mladineo, Marina Crnjac, Amanda Aljinović

Original scientific paper published in conference proceeding and presented on international scientific conference LSS 2018 The 3rd International Scientific Conference “Lean Spring Summit” (LSS 2018) took place from May 24th to may 25th 2018 in OpatiUniversita production, LEAN management and Industry 4.0. During the transition period of industrial enterprises, the service sector, public administration, and public sector, scientific institutions will have very important role in the area of R&D, and in the increase of the innovation potential of society. The conference will provide the insight in new developed concepts, procedures and products which are necessary to achieve the Industry 4.0 level.

Abstract Recent advances in Information and Communication Technologies (ICT), together with the concept of Cyber-Psychical System  global market. Production in high-volume batches is replaced with high-mix/low-volume production, which demands excessive information flow throughout production facilities. Following the balancing process of an assembly line reported in this article, a concept for industry 4.0 elements implementation in order to establish cognitive assembly line is presented. This paper deals with the process mapping, balancing the assembly line, and defining basic Industry 4.0 elements towards assembly line for product variety. Keywords: Balancing an assembly line, Industry 4.0, production variety, Information and communication technologies.