Implementacija sistema nadzora strojne obdelave v proizvodni proces

UNIVERSITY OF LJUBLJANA Faculty of Mechanical Engineering

Implementacija sistema nadzora strojne obdelave v proizvodni proces

Diplomska naloga Visokošolskega strokovnega študijskega programa I.

stopnje STROJNIŠTVO

Implementing of Machine Production Monitoring System into the Production Process

Final Thesis of the University Study Program I. level MECHANICAL ENGINEERING

Emil Buh

Ljubljana, August 2021

UNIVERSITY OF LJUBLJANA Faculty of Mechanical Engineering

Implementacija sistema nadzora strojne obdelave v proizvodni proces

Diplomska naloga Visokošolskega strokovnega študijskega programa I.

stopnje STROJNIŠTVO

Implementing of Machine Production Monitoring System into the Production Process

Final Thesis of the University Study Program I. level MECHANICAL ENGINEERING

Emil Buh

Mentor: Assoc. Prof. Davorin Kramar PhD.

Ljubljana, August 2021

Kandidat Emil Buh VISOKOOLSKI STROKOVNI TUDIJSKI PROGRAM I. STOPNJE STROJNITVO: VS 11918

NASLOV TEME: Implementacija sistema nadzora strojne obdelave v proizvodni proces ANGLEKI NASLOV TEME: Implementing of Machine Production Monitoring System into the Production Process

Sistemi nadzora proizvodnih procesov so v Sloveniji ge vedno v veliki meri izvajani roëno. V strmenju k osvojitvi nael Industrije 4.0, so potrebne raziskave in implementacije sistemov avtomatiziranega nadzora proizvodnje (SANP). Ker so ti sistemi ge razmeroma novi in malo razirjeni, naj bodo v skiopu tega diplomskega dela èim bolje predstavljeni. Cilj diplomskega dela je implementacija izbranega sistema v proizvodnjo ter analiza pridobljenih podatkov iz proizvodnih procesov. V delu naj bo diskutiran sam proces implementacije in uporabnost pridobljenih podatkov ter predstavjene prednosti in slabosti uporabe taknega sistema.

Delo naj vsebuje:

pregled literature na temo SANP opis in primerjavo izbranih SANP implementacijo izbranega SANP analizo pridobljenih podatkov

Diplomsko delo je treba oddati v jezikovno in terminoloko pravilni slovenèini.

Rok za oddajo tega dela je gest mesecev od dneva prevzema.

Production monitoring systems in Slovenia are still largely performed manually. In an effort to move towards the principles of Industry 4.0, research and implementation of machine production monitoring systems (MPMS) is required. Since these systems are still relatively new and not widely used, this thesis aims to introduce them as best as possible. The aim of the diploma work is to implement the selected system in production and analyse the data obtained from the production processes. The thesis will discuss the implementation process and the usability of the obtained data and present the advantages and disadvantages of using such a system.

The work should include:

Review of MPMS literature

Description and comparison of selected MPMS Implementation of the selected MPMS

Analysis of the obtained data

The master thesis must be written in standard English. The thesis must be submitted six months after it was accepted.

Mentor:

izr. prof. dr. Davorin Krarnar

Podpisani sem temo prevzel v Ljubljani dne, ^{6. 7. 2021}

Emil Buh

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Acknowledgements

I would like to express my sincere gratitude to my mentor, Assoc. Prof. Davorin Kramar PhD., who encouraged me throughout the journey of writing this thesis. From the very beginning he took time from his schedule for meetings and phone calls, to answer my questions and guide me in research.

Special thanks to Prof. Jana Petrů, Ph.D., multi MSc., M.A., who as a Head of Department of Machining, Assembly and Engineering Metrology at Visoka Škola Banska at Technical University of Ostrava suggested the topic and enabled research in the laboratory of her department. Thank you also to Jiři Jančijuk as the VŠB TUO IT specialist.

The technical contribution of Sandvik Coromat representatives, Mr. Jaroslav Suga and Mr.

Amel Hadzic is truly appreciated.

Last but not least, I would like to thank my wife, Tjaša. You kept me going.

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Declaration

I, the undersigned Emil Buh, student of the Faculty of Mechanical Engineering at the University of Ljubljana, with registration number 23180305, author of the written final work of studies, entitled: Implementing of Machine Production Monitoring System into the Production Process,

DECLARE that

1.* a) The written final work of studies is a result of my independent work;

b) The written final work of studies is a result of own work of several candidates and fulfils the conditions determined by the UL Statute for joint final works of studies and is a result of my independent work in the required share;

2. The printed form of the written final work of studies is identical to the electronic form of the written final work of studies;

3. I acquired all the necessary permissions for the use of data and copyrighted works in the written final work of studies and clearly marked them in the written final work of studies;

4. During the preparation of the written final work of studies I acted in accordance with ethical principles and obtained, where necessary, agreement of the ethics commission;

5. I give my consent to the use of the electronic form of the written final work of studies for the detection of content similarity with other works, using similarity detection software that is connected with the study information system of the university member;

6. I transfer to the UL – free of charge, non-exclusively, geographically and time-wise unlimited – the right of saving the work in the electronic form, the right of reproduction, as well as the right of making the written final work of studies available to the public on the World Wide Web via the Repository of the UL;

7. I give my consent to the publication of my personal data included in the written final work of studies and in this declaration, together with the publication of the written final work of studies;

8. I give my consent to the use of my birth date in COBISS record.

* Choose a) or b).

In Ljubljana, 3. 8. 2021 Student's signature: __________________

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Abstract

UDC 658.52.011.56(043.2) No.: VS I/918

Implementing of Machine Production Monitoring System into the Production Process

Emil Buh

Key words: production monitoring monitoring system mechanical treatment

production automatization industry 4.0

Production monitoring systems in Slovenia are still largely performed manually. In the quest to move closer towards Industry 4.0, further research in the implementation of machine production monitoring systems was needed. Since these systems are still very new and not widespread the implementation of the selected system (in cooperation with the faculty laboratory of the Technical University of Ostrava in the Czech Republic) and the advantages and disadvantages of using such a system in production was presented. Based on the obtained data from the machine production monitoring system, possible improvements on the given production and the process of implementation in the production process itself were discussed. The bachelor thesis includes the review of machine production monitoring systems literature, description and comparison of the three selected systems, description of the implementation of the selected system and analysis of the obtained data.

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Izvleček

UDK 658.52.011.56(043.2) Tek. štev.: VS I/918

Implementacija sistema nadzora strojne obdelave v proizvodni proces

Emil Buh

Ključne besede: nadzor proizvodnje sistem nadzora strojna obdelava

avtomatizacija proizvodnje industrija 4.0

Sistemi nadzora proizvodnih procesov so v Sloveniji še vedno v veliki meri izvajani ročno.

V strmenju k osvojitvi industrije 4.0, je bila potrebna raziskava implementacije sistemov nadzora strojne obdelave. Ker so ti sistemi še zelo novi in ne razširjeni, so bili v sklopu tega diplomskega dela predstavljeni, prav tako je bil predstavljen potek implementacije izbranega sistema (v sodelovanju s fakultetnim laboratorijem Tehniške univerze v Ostravi na Češkem) ter prednosti in slabosti uporabe takšnega sistema v sami proizvodnji. Prav tako, so bili na podlagi pridobljenih podatkov iz sistema nadzora strojne obdelave komentirane možne izboljšave na podanem primeru proizvodnje ter diskusija o samem procesu implementacije v proizvodnji proces. Diplomsko delo vsebuje pregled literature na temo sistemov nadzora strojne obdelave, opis in primerjavo treh izbranih sistemov, opis implementacije izbranega sistema ter analizo pridobljenih podatkov.

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Table of Contents

Acknowledgements ... v

Declaration ... vii

Abstract ... ix

Izvleček ... xi

Table of Contents ... xiii

List of Figures ... xv

List of Tables ... xvii

List of Used Symbols ... xix

List of Abbreviations ... xxi

1. Uvod ... 1

1.1. Ozadje problema ... 1

1.2. Cilji ... 2

2. Introduction ... 3

2.1. Statement of the Problem... 3

2.2. Objectives ... 3

3. Machine Production Monitoring Systems (MPMS) ... 5

3.1. Definition of MPMS ... 5

3.2. History and Development of MPMS ... 8

3.3. Advantages and Disadvantages of MPMS ... 10

3.4. Examples of MPMS ... 12

3.4.1. Sandvik CoroPlus Machining Insights (SCMI) ... 12

3.4.2. Telos d.o.o. - BeeSense Manager System (BSMS) ... 14

3.4.3. DMG MORI – CELOS - Messenger (DMCM) ... 16

4. Implementation of SCMI System ... 19

4.1. Description of the Machining Infrastructure and the Facility of Installation ... 19

4.2. Installation of SCMI System ... 23

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4.2.1. Installation Start-up Meeting ... 24

4.2.2. Factory Installation Preparation ... 25

4.2.3. Installation Meeting ... 31

4.2.4. Accessing SCMI ... 32

4.2.5. Configuration of SCMI ... 34

4.2.6. Calibration of SCMI ... 38

4.3. SCMI Data ... 39

5. Outcomes and Discussion ... 41

5.1. SCMI Data Analysis ... 41

5.1.1. Processed Data Charts Presentation ... 41

5.1.2. The Received Data Outcomes ... 43

5.1.3. Using the Data to Improve the Production ... 44

5.2. Implementation Outcomes ... 45

5.3. Comparison of Selected MPMS... 45

6. Conclusion and Points for Improvement ... 49

7. Zaključek in možnosti za izboljšave ... 53

References ... 57

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List of Figures

Figure 4.1: DMG Mori DMU 50, five-axis CNC milling machine... 21

Figure 4.2: CNC DMG Mori NLX 2500MC lathe machine. ... 22

Figure 4.3: Tajmac KMX 432 CNC lathe. ... 23

Figure 4.4: Steps that must be taken during the implementation process [19]. ... 23

Figure 4.5: The connection of the machine to the laboratories network. ... 26

Figure 4.6: Windows Command Prompt Software (CMD). ... 27

Figure 4.7: CMD – Current IP Address Configuration. ... 28

Figure 4.8: Setting the Static IP Address. ... 29

Figure 4.9: The input of the command to the windows command prompt. ... 30

Figure 4.10: The result of the input command for open port confirmation. ... 30

Figure 4.11: The predicted position for the operator’s computer tablet on the DMG MORI SEIKI controller... 31

Figure 4.12: Login window to SCMI web-application. ... 32

Figure 4.13: First page in SCMI web-application. ... 33

Figure 4.14: Create user definition board. ... 35

Figure 4.15: Three shift, final definition of the calendar for the whole week. ... 36

Figure 4.16: Activity creation in SCMI user interface. ... 37

Figure 4.17: Final calibrating of the SCMI system. ... 38

Figure 4.18: Example of the output chart for the machine production on the DMG MORI NLX2500 lathe machine. ... 39

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List of Tables

Table 3.1: Typically collected data items with the SCMI monitoring system [19]... 14

Table 4.1: Machine Tools in the department. ... 20

Table 4.2: Basic characteristics of the DMG Mori DMU 50 milling machine [26]... 20

Table 4.3: Basic characteristics of the DMG Mori NLX 2500MC/700 lathe machine [27]. ... 21

Table 4.4: Basic characteristics of the Tajmac Manurhin KMX432 lathe machine [28]. ... 22

Table 4.5: Tasks and responsibility defining list [19]. ... 24

Table 4.6: Required Minimum Computer or Server Configuration [19]. ... 26

Table 5.1: Colour Code description. ... 42

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xix

List of Used Symbols

Sign Unit Meaning

A P Q

%

%

%

Availability Performance Quality

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List of Abbreviations

Abbreviation Meaning BSMS

CAD CAM CIM CMD DMCM ERP FMEA GUI ICT IoT ISO IT JIT LAN MES MPMS MRP MRP II OEE PDT RAM ROM SCMI SSH UDT

VSB – TUO

BeeSense Manager System Computer-Aided Design

Computer-Aided Manufacturing Computer-Integrated Manufacturing Command Prompt Software

DMG MORI CELOS Messenger Enterprise Resource Planning system Failure Mode and Effects Analysis Graphic User Interface

Information and Communication Technology Internet of Things

International Standard Organization Information Technology

Just-In-Time method Long Area Network

Manufacturing Execution System Machine Production Monitoring System Materials Requirements Planning Manufacturing Resource Planning Overall Equipment Effectiveness Planned Downtime

Random Access Memory Reading Only Memory

Sandvik Coromat Machining Insights Secure Shell – secure remote login protocol Unplanned Downtime

Visoka Skola Banska – Technical University of Ostrava

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1

1. Uvod

Proizvodnja industrija se že od nekdaj bojuje z izgubami zaradi planiranih zaustavitev, ne planiranih zaustavitev, manjših zaustavitev, prepočasnih obdelovalnih ciklov, izmeta ob zagonu in izmeta med proizvodnjo. Z natančnim sledenjem vseh aktivnosti med proizvodnjo lahko pridobimo veliko informacij, ki izboljšajo preglednost procesov in omogočijo, da lažje organiziramo samo proizvodnjo z večjo točnostjo in manj izgubami. Na podlagi zavedanja pomembnosti informacij o procesih v proizvodnji potrebujemo zagotoviti ustrezen način za čim večji in delovno neintenziven zajem podatkov.

1.1. Ozadje problema

Najosnovnejši način zbiranja podatkov o proizvodnih procesih je sprotno beleženje dogodkov ali pisanje dnevnika. Dnevnik sledi seriji izdelkov po celotnem proizvodnem procesu. Na koncu proizvodnje ali tudi med proizvodnjo, nadzornik proizvodnje ali za to zadolžena oseba, zbere dnevnike in podatke vnese v informacijski sistem z namenom naknadne ročne analize efektivnosti proizvodnega procesa. Vnos podatkov se po navadi opravi na koncu vsake izmene ali se podatki o proizvodnji neke serije vnesejo v sistem po končani seriji. Obstajajo tudi možnosti računalniških postaj v proizvodnem obratu, kjer je mogoče nekatere podatke vnesti že neposredno ob začetku ali ob posameznih korakih serije.

Tako se lahko prihrani nekaj časa pri eliminaciji podvajanja procesov [1].

Ta način zbiranja podatkov je zelo delovno intenziven in zato posledično povečuje proizvodno ceno.

Pri optimizaciji stroškov proizvodnje se osredotočamo na lociranje in znižanje vseh vrst izgub v procesu. Zaradi nenehno razvijajočih se računalniško podprtih tehnologij je zbiranje informacij lažje in hitrejše kot kdaj koli prej. Danes je na trgu kar nekaj podjetij, ki so razvila svoje sisteme za učinkovitejše sledenje procesom proizvodnje ter za njihovo večjo transparentnost. Ti sistemi delujejo po načinu samodejnega zbiranja podatkov. Nekateri od sistemov so samo programsko nadgrajeni in zaradi vseh merilnih senzorjev, ki so že nameščeni na novejših strojih, ne potrebujejo dodatne strojne opreme.

Uvod

2

1.2. Cilji

V tej diplomski nalogi se bomo osredotočili na implementacijo izbranega sistema nadzora strojne obdelave (SNSO) na strojih ter analizirali pridobljene podatke s pomočjo sistema za zbiranje podatkov v realnem času. S pomočjo obdelanih in grafično prikazanih podatkov bomo podali analizo opazovane proizvodnje ter možnosti za njeno izboljšavo.

Analizirali in raziskali bomo različne sisteme nadzora strojne obdelave z njihovimi prednostmi in slabostmi.

Z izbranim integriranim sistemom bomo predstavili postopek implementacije strojne in programske opreme ter analizo zbranih podatkov.

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2. Introduction

The manufacturing industry is struggling with the losses such as planned stops, unplanned stops, small stops, slow cycles, start-up rejects and production rejects. With precise tracking of all the activities in the production, we could get a much better overview of the processes and organize the production with bigger accuracy and with fewer losses. That is why information and data about the processes are essential and we have to provide an efficient way of collecting them.

2.1. Statement of the Problem

The most basic way of production processes data collecting is by writing a journal. The production worker records the information on the paper charts which follow the product series throughout the production process. At the end of the production or in between the individual steps, the production supervisor or importer collects the charts and inputs the data into the information system with the aim of manual analysis of the effectiveness of the production processes. The input of the data is usually done after each shift. There are also computer stations in the production facility where some basic data can be input directly into the information system from the station, thus eliminating the duplication of processes [1].

This way of collecting data is very labour-intensive and makes the production price higher.

The big focus is to eliminate the unwanted production costs. Due to ever-evolving computer- aided technologies, information collection is getting easier and faster than ever. To avoid the losses from ineffective data collection, various companies developed systems of automatic data collection. Some of them are almost only software-based upgrades and due to all measuring sensors already installed on the new machines, do not need any extra hardware.

2.2. Objectives

In this paper, we will focus on the implementation of the chosen machine production monitoring system and we will analyse the received data by collecting the data from the machines in real-time. With the help of processed and graphically represented data, we will analyse the production and provide suggestions for improvement.

Introduction

4

We will analyse systems to control the production processes and present different production control systems with their pros and cons.

With the chosen integrated system, we will present the process of needed hardware and software integration and the analyses of the collected data.

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3. Machine Production Monitoring Systems (MPMS)

In this chapter, we will take a look at what MPMS are and how they came to be. We will investigate the benefits and disadvantages of it. Additionally, we will take a closer look at a few selected systems – Sandvik CoroPlus Machining Insights, Telos d.o.o. BeeSense Manager System (BSMS) and a subsystem of DMG MORI CELOS – Messenger (DMCM).

3.1. Definition of MPMS

The production process monitoring is not something new. It is a necessary activity for optimal production planning, to have as much correct data about the real-time production, as possible. In the past, the monitoring was done only manually by observers or operators filling up the forms about the produced parts and suggestions. Today, with more complex machining operations and available technology, we attempt to make it as automated as possible. This way, we can cover most related data and collect the data that can improve our productivity. This makes the collection of data and its processing cheaper - due to the usage of computer power rather than human labour.

By machine production monitoring, we are mainly collecting the data about produced parts, production times, stopping times, maintaining times, temperature, vibrations, etc. In the evolving “Industry 4.0”, we are doing this with the help of the sensors which measure and collect the data which are transformed from analogue to digital form. Furthermore, by the connection to the computer software they are processed and evaluated. The whole part together, if we use it to monitor the machine equipment, we call an MPMS.

Automated production monitoring is one of the steps toward “Industry 4.0” which is an often-mentioned name for the 4th industrial revolution. The “Industry 4.0” is defining a new grade of the organization and controlling over the entire value chain of the life cycle of products, going towards the individual customer requirements [2]. In the simple understanding, “Industry 4.0” is going toward the implementation of the digital systems in the industrial processes to maximize the control and effectiveness of those and minimize the waste and human labour. Thus, maximizing the individual requirements of the targeted group.

Machine Production Monitoring Systems

6

The production data monitoring can be categorized into two major status groups of collected data: »Status of resources« and »Status of jobs« [3]. In this work, we will focus on the status of jobs. Machine production monitoring is related to the data of individual completed operations, estimated production time, sequences, etc. The information about the order flow for the improvement of the production sequences is provided by the status of jobs.

MPMSs that we will discuss in this paper are based on the Internet of Things (IoT) system that is collecting digital data or transforming analogue data into digital data and then forwarding them via the intranet or possibly even the internet connection to the main processing computer. This computer can be located at the site of the installation of the systems, or the processing power is provided by the providers of the systems. In the second case, all the data is sent to the provider of the system. The customer receives only the processed data ready to observe. The main goal of the systems is to collect and present real- time data from the production manufacturing machines.

The Internet of Things (IoT)’s main purpose is to connect and exchange data over the communication network. It is evolved based on Information and Communication Technology (ICT). For data collecting, the IoT system has embedded sensors, computing devices to process the data and algorithms, and physical objects known as "the Things" with the ability to collect and transfer all the data without any human interaction involved. Most IoT devices require only one-way data transfer but in the meaning of two-way; the system is able to control the machine or the production line where the two-way data transfer is mainly used [4].

The MPMSs need only one-way data transfer as a result of only collecting and observing the data. In those systems, the main goal is to collect the data and process them into the information for organizational and managerial use for better optimization, to determine the effectiveness and understanding of the production behaviour.

Information and Communication Technology (ICT) is the name for the systems based on the logic functions of Boolean algebra. To make Boolean algebra effective in practice, on and off electrically controlled switches, so-called transistors in integrated circuits are used [5].

Boolean functions are generally called logic gates. By clever design of such gates, the computing functions can be constructed. By the logic gates and the transistors, we can further construct the three central computer elements of the ICT’s that are needed for its functional operation: data processing, information storage, and communication. The ICT system cannot run only by its hardware logic gates. For proper operation firmware is needed which is situated between hardware and software and is a piece of code loaded onto the non-volatile memory. We must mention that for the proper operation of the ICT systems, at least two different memory systems are needed. The first one being where the firmware is loaded and is reading only memory (ROM) that is non-volatile memory, and the second that is needed for program processing and is named Random Access Memory (RAM) which is volatile memory. The firmware makes the system of logic gates designed into a chip, flexible to individual possibilities of data processing. To add the higher level of abstractions and concepts to the hardware, the different operating systems software are used [6]. To add more advanced possibilities to the final ICT system, the layering of ICTs is possible by the device drivers which take care of the proper connection and understanding between each other [7].

The production monitoring systems can be extremely useful at detecting the bottlenecks, time losses, and their reasons, and are a reliable source of data for calculation of the Overall Equipment Efficiency (OEE) by its automated and semi-automated data collection about the availability, performance, and quality of the production. Some data, such as time counts and

Machine Production Monitoring Systems

7 produced parts, are collected automatically while others, such as broken parts, or undefined times, must be defined by the operators through the user interface software at the production station. In this case, there is no need for manual data collection at the production stations - in the meaning of manual input by the pencil to the provided spreadsheet charts. Even the needed data for enriching the information about the stop time or the broken parts are done faster, only by a few clicks, in the user-friendly software environment.

OEE is a tool to calculate the overall equipment efficiency based on the three main categories of losses: Availability, Performance, and Quality. It helps to understand what is limiting the machine and where we must act to improve the performance. In Availability losses, we categorize the breakdown and change over losses. To performance losses we categorize minor stops and reduced speed and into quality losses we categorize crap-rework-yield. The OEE is calculated by the following equation (3.1), where the symbol A stands for availability, symbol P for performance, and symbol Q for quality. The OEE is simply the product of all three parameters in percentage [8].

𝑂𝐸𝐸 = 𝐴 × 𝑃 × 𝑄 [%] (3.1)

The OEE evaluation is done in five main steps. In the first step, we must select the machine, where we will perform the OEE calculation. By involving the operators, we assemble a cross-functional team in the second step. The team will assure the correct execution of the data collection in the third step. Though means of collecting data manually, there is, for efficient and reliable collection of the data, a need for daily meetings that involve the data- collecting team. In the case of MPMS daily meetings can also be held to discuss the correct input of reasons for the stoppage or for deepening the knowledge about the stops. But those meetings can be, due to less input fail possibilities, more efficient and shorter. In step number four, we are analysing the collected data and graphs that we can discuss in the next morning's meeting. Step number five is regarding the implementation of the actions for improving the OEE discussed or proposed at the meetings or by managerial staff [8].

With the calculation of OEE, where we closely observe and analyse all the collected data, we can build the Failure Mode and Effects Analysis (FMEA). The Failure Mode and Effects Analysis or FMEA is an approach widely used in engineering to define, identify, and eliminate already known or potential failures, problems, and errors. The method is used on the design, processes, or services before they reach the customer [9].

When we already detected some possible problems from the production, we can now clearly define the size of the problem and how to deal with eliminating it in feasible steps. Some of the principles of the FMEA are integrated in the software itself. For example, if the machine is not operating for some time, the SCMI automatically sends a message, following the predefined rules of troubleshooting in the software, to the user.

In our case, the FMEA can be used in the MPMS itself for self-resolving the machine status failures or stops. In case of stop times that are too long, the system or operator follows the FMEA and checks the possible reasons for the stoppage. In some scenarios, the solution from the FMEA is to inform the operators or the management of the current machine status.

When the calculated probability for a breakdown reaches a critical level of possible failure, the software informs the management or maintenance team to plan the service of the machine, so the production can be affected as little as possible [9].

Machine Production Monitoring Systems

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3.2. History and Development of MPMS

The need for production monitoring was from the beginning of the production processes.

Humans were always monitoring their work and in the need of using the least energy for some job to be done, they were trying to optimize the current processes. The job of supervising was mainly done by the appointed supervisors as it is still today. If we focus on the production in the industry, there were many researchers even before the big scale automotive industry erupted in the 19th century. Frederick Winslow Taylor was monitoring and studying the time and how the tasks could be done faster in production. Frank Bunker Gilbreth and Lillian Gilbreth were studying motion and time to determine which motion takes less time and is as much as effective as possible [10]. The observers were monitoring its current production and validating its advantages and disadvantages. By the manually collected data, they could define the problems of slow production and long maintenance times and later evolve the ideas how to fasten them up.

Through the evolution of the production processes, the time consumption, and waste production lower. Additionally, the product prices became lower which causes more affordable prices for bigger market groups and furthermore, increases production capacity needs.

With different approaches finally in 1910, the inventor of the moving assembly line Henry Ford assembled the pieces of individual researchers. He and his team of engineers then started studying the production management by means of the most efficient movements, space organization as the main goal, to cut down the production time consumption. At that time, all the production machines were manual and many of them were specially made for the individual operation of the car manufacturing needs. They figured out that the prices of the products drop if the production time drops, and it makes the product more competitive.

The price of the product can be dropped by the efficient use of the space in the factory and in the case of early Ford production this was exploited to the very limit. They mention that sometimes there was hardly any space for workers to get to the machine, yet the working space needed for a worker to move the labouring moves on the machine was not affected.

They continued with the production time cuts at the machining times by adding more operations at one machine move. For example, when grinding the engine block, all 4 cylinders can be grinded together instead of one per time. The time of the process for the whole grinding of one engine was cut down to one-quarter of the starting time. The machines made a huge cut down on the consumed labour time for some products and at the same time increased the quality and repeatability [11, 12].

Over the years the production process supervising has evolved. Even if the supervisor job is at the bottom of the managerial hierarchy pyramid, it has a significant role in the production floor efficiency. Before the second world war, in the production processes only skilled, male manpower was used. However, between the war and especially after 1942, more and more women were employed in positions of previously male dominated work. When dealing with female workers, the supervisors of the production processes had to deal with another aspect of labour supervision. Previously, the supervisors were rougher on some occasions, they even used physical force to reinforce the hierarchy on the production floor. However, when working with female workers this changed. The supervisors treated the workers now more respectfully, confirming their individuality which in turn helped them to lead the production more efficiently. This historical lesson can be easily translated to nowadays and the supervisors' role in presenting and implementing new technology. As we focus on the SCMI

Machine Production Monitoring Systems

9 or supervising the production processes technologies, it is crucial that this technology is presented to the operators in a proper manner. If the new technology in the production floor is not accepted from the operators properly, it can lower its effect. When looking at the investment in these technologies this would mean an unnecessary loss of capital [13].

With the evolution of the computer technology from the first systems, based on the mechanical mechanisms in 1930, to the all-digital nowadays, the data processes became much faster, cheaper, and less human labour consuming.

The first overall manufacturing supervising and planning concept originates from the 1960s as Computer-Integrated Manufacturing (CIM). It is not a specific, individual technology but rather a combination of available technologies, such as CAD-CAM (Computer-aided design and Computer-aided manufacturing), MRP/MRP II (Material requirements planning and its updated version II), JIT (just-in-time method), under the main CIM system. CIM is a technology mainly used for managing [13].

CAD – Computer-aided design is one of today's indispensable tools in all engineering branches. Through this technology, we use the computer software and hardware in interactive engineering drawing and storage of designs for manufacturing. With the help of CAD engineering, the designers complete the layout, geometric dimensions, projections, rotations, magnifications, and cross section views of a drawn part or a part in relation to the other parts. This technology or software is of a big help and provides great savings due to much simpler designing, building, and testing method of the designed parts or systems, in comparison to the traditional designing before the use of the CAD systems [14–18].

CAM – Computer-aided manufacturing is the software which, with the input of the CAD digital file, directly programs the production machines or other equipment which is run by the numerical control. In this case, the CAD file is used as the source of the information feed to the CAM software. Systems, where the CAD files are used in the production of CAM programming, are named CAD-CAM. A combined system facilitates the planning, operation, and control of a manufacturing facility [14–18].

MRP – Materials Requirements Planning is the system that calculates the inventories and scheduling in the production. It is used for planning the future of manufacturing and purchases all the needed orders for the effectively completed orders within the production schedules. The great benefit of the system is its possibility for the JIT (Just In Time) system of manufacturing, where we eliminate the storage costs by ordering the needed components right in time when they are needed in the production [15, 18]. With the evolution of this system, the connection between marketing, management and production control improved greatly. In case of good feedback from the production facilities, the effectiveness of the MRP system is even greater. The MRP was later upgraded to the wider system named MRP II – Manufacturing Resource Planning. Based on the line organization, the software integrates the MRP system and makes it a closed-loop managing of the production needs, for forecasting and sales, design engineering, purchasing and receiving, production activity planning, maintenance planning, distribution planning and cost accounting [15, 18].

The main goal to be competitive in the field of production is to invent new ways of producing parts or to get as accurate a schedule as possible at a single machine. Then we can analyse it to find the bottlenecks or the repetitive issues that could prevent the machine from stopping the production.

The manufacturing industry has since the beginnings been struggling with the losses such as planned stops, unplanned stops, small stops, slow cycles, start-up rejects and production

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10

rejects. All those losses are well known in the industry. In the early '60s, there was a standard OEE developed. The OEE has been widely used for measuring manufacturing productivity.

It is designed to improve the performance and reliability between facilities [19, 20].

While more and more technologies are digitized in the production process, it makes a reasonable choice to digitize the basic information about the feedback from the production.

Connecting all the factors that affect the production into one system is the goal of "Industry 4.0" which we are going towards and aiming for. Building the manufacturing or production lines with human independent processes, we need all the activities registered in the digital or computer able-to-read language. To enable this, MPMS automatization is needed.

Production managers were, before the evolving digital computer technology, struggling with the recording of all the exact times of the machine stops and operations. The first automatic monitoring systems in that field, to record the stopping times and the operating forces, and other needed effects, were the parallel measuring systems that were upgraded to the machines after the installation into the production processes. Those systems helped to record and prevent greater damage to the machines by sensing the activities on them. With the collected data it was later possible to analyse the production of the individual process through newly integrated sensors.

Automatic production monitoring is the main goal of the production industry nowadays. We are lowering the losses of the production through higher accuracy in the process monitoring.

There are many companies today that use these automatic control systems to assure the most reliable data possible and eliminate the losses as much as possible [21].

An important fact is that using real-time insights in the production process eliminates the paperwork as it is a paperless reporting approach. It has many benefits in labour consumption and waste generation. The value of real-time production monitoring is in its fast feedback that we can get and act on the very beginning of the issue while the costs for acting are still relatively low.

3.3. Advantages and Disadvantages of MPMS

While we encounter many benefits of the MPMSs, we must be aware of the disadvantages.

In this chapter, we will define both.

Regarding the aforementioned manual collection of the data about the production process (considering the speed and time consumed for it), by using the MPMSs this manual data collection is not needed anymore. All the data collection is done automatically by the system sensors and stored on the cloud database.

While the system is fully established on the shop floor, optimized production planning and streamlining can be achieved by constant production flow control and information analysing.

By the same means, higher production efficiency, quality and quantity can be achieved.

Regarding almost instant production process feedback in the system, the production process became very transparent. All the stops or inefficient work can be seen on the timelines and the counters already at the time of the production planning or at the time of the effectiveness analysis, so there are no possibilities for irresponsible operating to become unnoticed. Using the available data, the OEE can be calculated much easier and up to date since all reliable needed information is readily available.

Machine Production Monitoring Systems

11 The main advantage of the system at the end is the savings. The saved money can be invested in the wellbeing of the operating staff or for the improvement of the working environment as, for example, free beverages for the employees, company family day celebration ceremonies, team-building opportunities etc. All of those will, in the long run, improve the overall work and productivity of the staff.

On the other hand, the disadvantages are the possibility of compromised data in case of breaking into the system. It could make not only the data visible to the third parties, but it might compromise the production due to dysfunctional system capacities.

It is very important, for achieving the highest possible system efficiency, that the users of the system are well introduced to it. Many systems in that case still rely on some part of manual data input of causes for stops that are demanded by the machine operators. If machine operators do not fully understand the need for this data, they can in some way sabotage the efficiency of the system. On the other side, there are the production managers or supervisors that are using the Graphic User interface (GUI) of the system to extract the needed information about production. If somehow, they do not fully understand the possibilities of the programs or their freedom, the software’s effective efficiency drops again. Due to the investment into the system and by the fixed costs that accompany the software subscription, we have to be sure that the possibilities of it are fully achieved and used.

In order to cover the fixed costs of the system subscription and the investment cost we have to be sure that the production efficiency can be achieved for at least so long that the system costs are covered. In case of choosing the system implementation we would go for only when we can ensure some savings. Connected, the production infrastructure must be big enough to cover the costs of the MPMS.

Overview of the Advantages and disadvantages of the MPMS:

Advantages

- No manual data collection (tracking time reduction), - Optimized production planning and streamlining,

- Through proper use of the collected data, we can higher the production efficiency, quality, and quantity,

- Visualization of production running specifications, - Production transparency,

- Fast feedback on optimization options, - Collected data ready for the OEE calculation, - Minimalization of running costs,

- Better wellbeing in the company due to possible higher wages due to savings.

Disadvantages

- In case of brake into the system, the information of the company can be compromised,

- Without good knowledge what to do with the collected information, the system could be considered useless,

- The shop floor must be big enough for it to be able to acknowledge the cost- efficiency effect and cover the running cost of the system,

- Extra fixed costs.

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3.4. Examples of MPMS

Today there are many possibilities on the market regarding the production monitoring systems. There are the big scale companies that provide more universal types of the systems and mostly small-scale companies that can provide you with more individual possibilities of the systems on each machine. In the following three chapters, we will present some of the machine monitoring systems currently available on the market.

3.4.1. Sandvik CoroPlus Machining Insights (SCMI)

Sandvik Coromat company, established in 1942, is part of the multinational Swedish group Sandvik and world’s leading supplier of tools and know-how to the metalworking industry.

They develop, produce, and supply the market with high-quality products. The company is represented in more than 150 countries in the world. In 18 of them, they also provide theory- based trainings for customers, distributors, employees, educators, and students. There are approximately 7600 employees around the world employed by the Sandvik Coromat company. The company claims more than 1800 patents in their products. On average they introduce 6 new products on the market every day. Sandvik Coromat company has received a certification for international standards such as ISO 26623 – tool holding systems, the ISO inserts and ISO 13399 standard [22].

Short Product Description

SCMI is a cost-effective solution which is easy to install and use. The goal of the system is to improve the production output and to reduce the waste. The benefit of the system is the elimination of the manual data collection for finding out the machine’s running efficiency.

With the use of analytics and the visualized real-time data presentation, the systems help to quickly and efficiently find ways to improve the performance of the production [19].

How SCMI Works

The system is deployed as a cloud-based application usually without any hardware installations required. In any case there is a need for a server at the factory but nowadays all the bigger factories already have it. The machines must be connected to the intranet network and further to the factory server. It works in three main steps.

The first step is totally autonomous without human need to intervene in data collection from the machines via the network. A software is installed on a factory server. The software collects data from machines through the factory network and sends them as compressed data to SCMI in the cloud. Processing power and cloud space is provided by the external company which has a contract to do so with the Sandvik Coromat company. For further improvement of the data definition, the operator can input extra manual description of the cause for stop via tablet interface [19].

The second step is the processing of the collected data. The data are automatically connected to the machine and presented in the form of charts and graphs. Extra description of all stops is provided. Processed data is then stored in a cloud which we can access through the up-to- date supported web browser [19].

Machine Production Monitoring Systems

13 The third step is the data analysis step. The web browser app is used for the graphic presentation of real-time and historic data. In the app, we can observe and point out the main causes for the stops or production slow down on each machine individually and define new stop causes or “tickets” to research the cause of slower production even deeper. The most often presented information about the machine and production is if the machine is currently running or not, stop causes, faults, and alarm reasons. There is the possibility to obtain insights to the optimization opportunities [19].

Implementation needs

The system can be implemented on machines younger than 10 years old via the connectivity standards MT-connect or OPC. Some machines are already ready to connect due to their MT-connect standard. An example of a machine like this is Okuma which uses OSP-P control. Other machines need an adapter that transforms the internal machine language to the monitoring system understandable one. There is a basic adapter for machines like Fanuc or Heidenheim and an advanced one for the machines from Siemens. The needed adapter is provided by the Sandvik Coromat company after providing the information about the machine upgrading park. Here are some examples of the machines that SCMI can be installed on. Together with the already mentioned ones, there are also the following: Mazak, DMG Mori Seiki, Doosan, Fagor, GF Agie Charmilles, Haas, LinuxCNC, FINS, MakerBot, Makino, Mitsubishi, Mitutoyo, MODBUS, NUM, OPOS, PCDMIS, ROS-Industrial, Sodick, Allen-Bradley (CNC), Balluff, ControlLogix and Toyo [19].

To implement the SCMI system we first need to provide information about the machine connectivity systems (OPS or MT-connect). If there is a machine with the system of MT- connect there is no need for any adapter and the machine can be connected directly to the intranet. In other cases, there is a need for the adapter to transform the machine data to standardized MT-connect data. After the channels for collecting the information from the machines are established and connected to the main server of the machine floor, the installation of the data collecting and compressing software is executed on the main machine floor server [19].

Data Collection and Presentation

The data collecting is done by the SCMI system every 1-4 seconds. The data collected on the machine depends on the possibilities of the machine and they can be obtained from the make, model, controller, year, and the selected option of the machine. The typically collected data items are stated in Table 3.1. They are later used for the graphic presentation in the form of charts (GREEN-YELOW-RED) or the state of the machine display and can be used by other information systems in the enterprise (for example ERP system) [19]. The colour system is based on the principle of green – no need for action, yellow – action could be needed soon or only check-up is needed, red – there is need for operator’s interference.

The presentation of the data is, as mentioned before, done by the web browser (Google Chrome, Mozilla Firefox) platform. After the completion of the installation process, the login details are sent to the user. For login and receiving the data, the hardware from which we access the web browser has to have access to the modem with the internet connection [19].

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Table 3.1: Typically collected data items with the SCMI monitoring system [19].

ACTIVE_AXES EXECUTION PATH_POSITION

ACTUATOR LINE POSITION

ANGLE LOAD PROGRAM

AVAILABILITY LOGIC_PROGRAM ROTARY_VELOCITY

BLOCK MOTION_PROGRAM ROTARY_VELOCITY_OVERRIDE COMMUNICATIONS PART_COUNT SYSTEM

CONTROLLER_MODE PATH_FEEDRATE TEMPERATURE EMERGENCY_STOP PATH_FEEDRATE_OVERRIDE TOOL_NUMBER

Pros

+ No need for major intervention to the machine,

+ No need for production to stop during the implementation process, + No need for one brand devices only.

Cons

- Based only on the already integrated sensors on the individual machine.

3.4.2. Telos d.o.o. - BeeSense Manager System (BSMS)

The BeeSense Manager System (BSMS) software is the supervising application developed by the Slovenian company Telos d.o.o. to optimize the production processes. The company defines its mission as the development and marketing of advanced telecommunication solutions. Their main products are solutions for wired, mobile, and wire-free Wi-Fi connectivity. The vision of the company is to become a leading regional provider of advanced IT solutions by the investments in research and development as well as own developed applications and new solutions. Their business partners are from various production industries, telecommunication operators, banks, public institutions, hotels, dealers, education institutions [23].

Short Product Description

BSMS system is based on the main software named BeeSense Manager. The software collects and already processes the collected data. Production data or machine operating data are collected by the external sensors or the adapter. The adapters are connected directly to the machine's control interface and then sent through the Wi-Fi connection to the connection ports and further to the software. The adapter on the machine is providing the possibility of connecting extra sensors to observe some other parameters if desired by the user. For now, the system offers only the external sensors connection but there is a possibility to connect to the machine integrated sensors.

How the BSMS Works

The machine we want to connect to the BSMS must be connected to the Zigbee adapter. In the basic setup, we can use only one adapter per machine if it has all the sensors that we need

Machine Production Monitoring Systems

15 already integrated. The adapter is directly connected to the machine controller which can be analogue, digital, or serial (RS232/485). If we do not use the integrated sensors, we do have a maximum number of sensors that can be connected to the Zigbee adapter [24].

If needed, there is a possibility with this system that we can connect extra sensors to the machine by installing company-provided, Zigbee sensors and optionally some extra adapters to make a final connection to the system [24].

All the adapters are then further connected to the Zigbee Digi Connect Port via the wireless connection. The Digi Connect Port makes the connection between the local wireless network and mobile or wired (LAN) network through which data is sent further to the Bee Sense Manager Software [24].

As mentioned, the software is the base of the system. It is installed on the Linux software- based computer, with access to the internet or LAN, in the control centre. The control centre is usually located in the company where the system is implemented. The software based on the Linux platform is used as the monitoring application which is receiving the incoming collected data from the machines, or sensors about the machine state. The software can receive data by more than one Digi Connect Port which means that we can control more production facilities from the same software. The data are processed in the application and saved or presented in the most user-friendly way for all the connected machines in the form of charts or graphs. From the output processed data, we can obtain the current status of the machines, working time, stops, shutdowns, service counter, general information about the machine, number of produced parts in the amount of time, length, and the number of the stops [24].

The software takes care of the notifications about the stops caused by the operator, alarms, need to interfere, need for regular maintenance, and overall production overview for the whole day, week, month. It can automatically report the machines or production status to the email post or the SMS [24].

Implementation Needs

For the implementation of the system, there is a need for at least one Zigbee adapter on a machine and in case of not using the integrated sensors, there is a need for external Zigbee sensors upgrade. For the adapter to be connected to the main software we need the Digi Connect Port which has to be further connected to the intranet or internet connection that is connected to the main computer. The main computer must have the BeeSense Manager installed on it. The installation, the configuration of the system as well as the introduction to the system are done by the system provider [24].

Data Collection and Presentation

We already described how the data are collected in the “How the BSMS Works” section above. Presentation of the data is done by the FMEA coloured rules in form of charts and action description history. The data is accessible through a web browser which makes it accessible also from a distance if the computer that has the BeeSense Manager application installed and is connected to the internet [24].

Machine Production Monitoring Systems

16 Pros

+ Mobility support inside,

+ No need for cable connectivity, less setup infrastructure, + Fully adaptable to the user needs,

+ Can be installed on a manual machine.

Cons

- Need for extra computer power for running the software.

3.4.3. DMG MORI – CELOS - Messenger (DMCM)

CELOS is software that connects the whole family of DMG MORI integrated applications.

The software was developed in 2013. The main idea behind the CELOS evolution is to integrate all the production relevant information to the system and connect it with the other companies existing systems such as ERP or Manufacturing Execution System (MES) directly with the CELOS [25]. The big advantage for the users of the system is that one can get highly automated data collection about the production processes and the production organization as well. It must be mentioned that the system works perfectly with the DMG MORI products. However, with different brands of machine park devices, the connectivity to the system can get complicated or even impossible [25].

Company Description

DMG MORI is a company that was established after the year of 2009 with the collaboration of the two technically advanced companies in machining machines production. The company DMG was established and based in Germany from as early as 1870 under the name of Gildemeister & Comp. The company MORI was established and based in Japan from 1948 onwards. The vision of both companies was to develop and produce high-quality and advanced machines for machining. In the past years, the development branched in the area of 3D printing and digitalization of the machine park to reach the "Industry 4.0" goals. The company has its own campuses for development and education of the new products and engineers [25].

Short Product Description

When describing the product, we must emphasise that in this case under the CELOS family of software, there are quite a few different software that are executing the functions as presented in the previous systems. However, in our definition of MPMS, there is one main sub-application that is observing and taking charge of informing the user about the current situation on the devices. This software is called DMG MORI Messenger V2.

The software makes the possibility to access the real-time production status anywhere using any internet-connected devices. In case of malfunctions, it can immediately send an e-mail or SMS report of the problem.

How CELOS MPMS Works

The software Messenger is collecting all the reliable data from the machine sensors or other saved data about the machine. Those data include information such as type, machine state via indicators, the timeline of the past states of the machine, name of actual NC program,

Machine Production Monitoring Systems

17 required, and the actual number of parts, elapsed time of the current and the last workpiece, as well as axis positions and loads.

All the data is then processed already on the site of the machine park where the application is activated and is not sent any further to the third-party companies. The software processes the data and makes them available through web browser applications.

The benefit of the CELOS system is the possibility of eliminating the costs by only purchasing the needed subprogram. If there is a need for the upgrade later, there are other two software available. One for analysing the production efficiency and one for monitoring the machine status in terms of maintenance.

Implementation Needs

For the implementation of the system, the hardware or the machine device from the DMG MORI group together with the activation of the system in the CELOS platform is needed.

There is a possibility to run the system on a few other controllers from Samsung and Heidenheim but not granted that it will work on machines from other producers. Before the implementation, there is a need for a clear statement of the machine park that the system would be implemented into.

Data Collection and Presentation

As mentioned, the data is collected directly from the machine-integrated sensors and processed in the sub-application. The results are represented in the coloured charts with the basic colour scheme of green-yellow-red that present the state and actions needed for various occasions.

Pros

+ Fast and simple upgrade of the system, + More possibilities for upgrading the software,

+ Integration of the MES and ERP systems with the software, + Machine maintenance status calculation,

+ Possibility to digitalize the whole production process to a full “Industry 4.0” level.

Cons

- For efficient use of the system, it is recommended to use only DMG MORI products,

- Not possible to implement on many machine devices from 3rd party producer.

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19

4. Implementation of SCMI System

In this chapter, we will focus on the implementation of the SCMI in the production process.

We will describe the facility where the system was implemented together with the machining infrastructure, the implementation process and what were the needs for implementation. We will describe the received information from the SCMI software.

4.1. Description of the Machining Infrastructure and the Facility of Installation

The implementation of SCMI will be carried out in the workshop of the Department of Machining, Assembly, and Engineering Metrology at the Faculty for Mechanical Engineering at the Technical University of Ostrava (VSB – TUO).

The department currently directs its strategic goals to science, research, and teaching related to the topics of engineering of production technology, additive production technology, and application of engineering materials.

In terms of scientific research and cooperation with practice, the department mainly focuses on the specific areas of machining difficult-to-machine materials, assessing the machinability of new construction materials, testing the toughness of machine tools in intermittent cutting conditions, testing the toughness of tool materials with higher brittleness, studying the cutting ability of super hard cutting materials, the study of surface layer properties of machined surfaces (surface integrity), experimental study of the cutting process, modelling of longitudinal turning according to temperature indication, modelling of surface grinding according to temperature indication, the operational reliability of machine tools, application of CAD/CAM systems in machining, etc.

The infrastructure of the observed department consists of four main groups of machine tools that are used for machining, metrology, measuring and digitalizing, and additive technology.

Table 4.1 shows the entire machine park of the department. In the end, we will focus only on the machines that were included in the SCMI implementation. The SCMI system will be implemented on the three CNC machines for machining: one milling machine (DMG Mori DMU 50) and two lathe machines (DMG Mori NLX2500/700, and Tajmac KMX432).

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Table 4.1: Machine Tools in the department.

Device Type of the Technology Working space

mm Model - WJ4025-1Z-Cobra-

PJ5AX-60°

CNC water jet 2500 × 2000

Kovosvit MCV 1270 (three axes) CNC milling machine 1270 × 610 × 720 Rexim RMX 3500 (three axes) milling machine 787 × 508 × 500 DMG Mori DMU 50 (five axes) CNC milling machine 650 × 520 × 475 Rexim proturn RLX1630 CNC/manual lathe machine Φ 400 × 760

Tajmac KMX432 CNC lathe machine Φ 36 × 410

DMG Mori NLX2500/700 CNC universal lathe machine Φ 366 × 705

DMG Mori DMU 50 is a five-axis CNC milling machine. The working area is 500 mm × 450 mm × 400 mm (X × Y × Z). It can run the main spindle with a speed from 20 up to 18000 min^-1 and can reach the tool moving speed in the X × Y × Z axis up to 24000 mm/min.

The machine has a 16 pockets capacity in the tool magazine. The maximum weight of the workpiece is 300 kg. Other specifications are provided in Table 4.2 [26].

Figure 4.1 shows the assembled machine DMG Mori DMU 50.

Table 4.2: Basic characteristics of the DMG Mori DMU 50 milling machine [26].

Clamping area 630 × 500 mm

Maximum tool diameter Φ 130 mm

Travel in X-axis 500 mm

Travel in Y-axis 450 mm

Travel in Z-axis 400 mm

Speed range From 20 – 18000 min^-1

Drive power (40/100% DC) 35/25 kW

Swivel range -5 til 110 °

Rotary axis 360 °

Maximum load 300 kg

Rapid traverse (X/Y/Z) 24000 mm/min

Tool magazine capacity 16 pockets

Cooling pump pressure 40 bar

Control system Heidenhain iTNC 530 HSCI

Clamping according to DIN 69 871 HSK-A63

Implementation of SCMI System

21 Figure 4.1: DMG Mori DMU 50, five-axis CNC milling machine.

DMG Mori NLX 2500MC/700 is a CNC lathe machine with driven tools. The working space is φ260 mm × 795 mm (X × Z). This machine has 12 tool positions and the given speed from the motor powering those tools is 6000 min^-1. The maximum spindle speed is 4000 min^-1. The machine can reach the tool moving speed in the X × Z axis up to 30000 mm/min. Other specifications are given in Table 4.3 [27].

Figure 4.2 shows the assembled machine DMG Mori NLX 2500MC/700.

Table 4.3: Basic characteristics of the DMG Mori NLX 2500MC/700 lathe machine [27].

Running diameter above the bed 787 mm

Running diameter above the support 541 mm

Max. turning diameter 366 mm

Max. turning length 705 mm

Travels in the X-axis 260 mm

Travels in the Z-axis 795 mm

Max. spindle speed 4000 min^-1

Number of tool positions 12

Max. speed of rotary tools 6000 (10000) min^-1

Machine spindle power (at 25/50/100%

load)

18,5 / 18,5 / 15 kW

Machine weight 5500 kg

Cooling pressure 18 bar

Postprocessor MasterCAM

Control system Mitsubishi M730BM

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22

Figure 4.2: CNC DMG Mori NLX 2500MC lathe machine.

Tajmac Manurhin KMX432 is a CNC lathe machine for higher productive processing. The maximum raw material diameter that can be processed is 32 mm or 36 mm at the length of 3000 mm. The machine is equipped with two spindles for machining from both sides with electric power of 3,7 and 5,5 kW. The machine is able to produce the entire, finished product from both sides. Maximum spindles speed is 10000 min^-1. The maximum machining length per stroke is 400 mm. The stroke of the main headstock is 420 mm. The machine has in total 6 processing axes (X1, Y1, Z1, Z2, and two rotary C1, C2). The milling is very efficient with a torque of up to 32 Nm. Other specifications are given in Table 4.4 [28].

Figure 4.3 shows the assembled machine Tajmac Manurhin KMX432.

Table 4.4: Basic characteristics of the Tajmac Manurhin KMX432 lathe machine [28].

Max. diameter of bar stock Ø 13 (16) mm

Spindle bore Ø 18 (19) mm

Spindle power kW 3,7 / 5,5 kW

Spindle power kW 2,2 / 3,7 kW

Spindle max. speed rpm - main 12 000 min^-1 Spindle max. speed rpm - counter 12 000 min^-1

Spindle stroke 130 mm

Number of CNC axes 4 + 2

Programming channels 2

Tools in cut at the same time max 2

Live tools power 1 kW