COPYRIGHT 2017 BY MUHAMMAD NAVEED-UL-HASSAN

Transcription

1 NICKEL SMELTER CONVERTER SLAG SKIMMING BASED ON THERMAL IMAGING A Dissertation Presented to The Engineering Institute of Technology by Muhammad NAVEED-UL-HASSAN In Partial Fulfillment of the Requirements for the Degree Master of Engineering in INDUSTRIAL AUTOMATION APRIL 2017 COPYRIGHT 2017 BY MUHAMMAD NAVEED-UL-HASSAN i

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3 TABLE OF CONTENTS List of figures.v Glossary of Terms vii Chapter 1. Introduction..1 Chapter 2. Background and the Problem Emissivity Thermal Imaging Characteristics of Infrared How the heat transfers Emission, reflection and transmission of infrared Principle of measurement by Infrared Thermography equipment Chapter 3. Literature/Previous Related Work Technology Introduction Research Paper s Results 19 Chapter 4. Methodology and Thermal Camera Trial Thermal Camera Visual Proposed Solution: Remote Skimming Remote Cabin Setup Improved Network Setup Camera Hardware and Installation..28 Chapter 5. Experimentations 29 Chapter 6. Network Design/Hardware Installation and Future work...32 Chapter 7. Results...35 Chapter 8. Conclusion..40 iii

4 Chapter 9. Appendix Network Layout Stress Level Test Thermal Camera Setup Screens Perceived stress test sheets Thermal Camera Trial Raw Data Skims without camera Raw Data Skims with camera Raw Data References 65 iv

5 LIST OF FIGURES Figure 1 Slag Pot View Using IP Camera... 1 Figure 2 Nickel Resources... 4 Figure 3 Nickel Smelting Process Flow Diagram... 6 Figure 4 Converter View from Across the Aisle and Inside of Existing Skimming Cabin... 9 Figure 5 The Existing Cabin s Door with Shattered Glass Window. The Tinted Glass used as Visual Assistance while Skimming Figure 6 Slag Pot View Using IP camera Figure 7 Electromagnetic Spectrum Figure 8 Emissivity Explanation Figure 9 Heat Transfer Figure 10 Emission vs Reflection vs Transmission Figure 11 Infrared Thermography Figure 12a Temperature Trends for MWIR Thermal Images Both for Steel and Slag Figure 12b Temperature Trends for MWIR Thermal Images for Slag (Detailed View) Figure 13 Thermal Camera Image Figure 14 Skim 1 in the Blow Figure 15 Matte and Slag Percentages Displayed in Bar Graph and Temperature Color Palette with Temperature Range on the Top Right Side Figure 16 Skim 3 in the Blow Figure 17 Skim 4 (High Grade or FINAL) in the Blow Figure 18 Skim 5 (High Grade or FINAL) in the Blow This Pot goes for Granulation Figure 19A Converter Slag Samples An Extract from Lab Report Figure 19B Converter Slag Samples Screenshot from HMI Screen v

6 Figure 20 Camera Screens in Skimming Cabin Figure 21 Camera Mount View from Across the Converter Aisle Figure 22 Thermal and IP Camera Mount View from the Skimming Platform Figure 23 Average Nickel Percentage in Skimmed Slag Without Camera Figure 24 Average Nickel Percentage in Skimmed Slag With Camera Figure 25 Perceived Stress Test Results Figure 26 Perceived Stress Test Result s Chart vi

7 GLOSSARY OF TERMS IP: Internet Protocol IRT: Infrared thermography NKS: Kalgoorlie Nickel Smelter FFM: Flash Furnace matte PPE: Personal protective equipment vii

8 ABSTRACT Nickel manufacturers have sought a reliable means of controlling the quantity of slag carried forward from the nickel making vessel for many years and a variety of solutions have been tried with a limited success. Thermal imaging presents an effective and reliable means of slag control. Thermal cameras are being used in the steel industry for over a decade, but the technology has not been utilized in the nickel industry. In this thesis, I have utilized Thermal Imaging Camera to monitor the percentage of Matte/Slag while skimming from the converter from the safety of a remote converter cabin, which is not located inside the crane aisle or next to the converter itself. As a part of this thesis, all the controls from the existing skimming cabin have been relocated to a new cabin, which is located away from crane aisle and provides a lot safer working environment for skimming operators. The operators have access to thermal image of the slag stream and normal IP camera visual of the equipment as well to perform slag skimming from the safety of a remote converter cabin. viii

9 CHAPTER 1. INTRODUCTION The Kalgoorlie Nickel Smelter (NKS) was commissioned in December 1972 and officially opened on 7th April Today, NKS can treat up to 110,000 tons of nickel-in-concentrate per annum with an average blend grade of 12 15% nickel. Between 100,000 and 110,000 tons of nickel-in-matte is targeted for production per annum. The matte has an average grade of 68% nickel, 2 3% copper and 1% cobalt. Approximately 500,000 tons of sulfuric acid is also produced each year. Primary nickel is produced from two very different ores, lateritic and sulfidic. In this case, the smelter uses the sulfidic ore to extract the Nickel and the main reason to use this kind of ore is the ore availability from contracted mine sites. Figure 1 Slag Pot View Using IP Camera. Flash smelting is the most common process in modern technology, but electric smelting is used for more complex raw materials when increased flexibility is needed. Both processes use dried concentrates. Electric smelting requires a roasting step 1

10 before smelting to reduce sulfur content and volatiles. Older nickel-smelting processes, such as blast or reverberatory furnaces, are no longer acceptable because of low energy efficiencies and environmental concerns. Flash smelting is a smelting process for sulfur-containing ores. Flash smelting with oxygen-enriched air makes use of the energy contained in the concentrate to supply most of the energy required by the furnaces. The concentrate should be dried before it is injected into the furnace. In a furnace based on electric smelting, the charged material is heated by means of an electric arc generated by electrodes. This type of furnace is economical only where there is abundance of electricity supplied by well-developed electrical grid and has a huge energy cost. Based on the energy cost comparison and the high sulfides in ore, the flash smelting is the most economical and a better choice. In flash smelting, at the smelter dry sulfide ore containing less than 1% moisture is fed to the furnace along with preheated air, oxygen-enriched air (30 40% oxygen) or pure oxygen. Iron and sulfur are oxidized. The heat that results from exothermic reactions is adequate to smelt concentrate, producing a liquid matte (45 52% nickel) and a fluid slag. Furnace matte still contains iron and sulfur, and these are oxidized in the converting step to sulfur dioxide and iron oxide by injecting air or oxygen into the molten bath. Oxides form a slag, which is skimmed off [1]. Nickel is rarely used by itself and the most common use is to mix it with other metals producing alloys that are very different from, for example, gold and copper. There are thousands of alloys in the market that contain nickel and each one of them 2

11 is developed to offer particular properties or conditions of use. The nickel content of these alloys varies quite a lot, for example, 1 3% for special engineering steels, 8 14% for stainless steels, 15 40% for special engineering alloys, 40 90% nickel for special alloys for the aerospace and electronics industries. It is a usual practice for special alloys to be recycled as the same special alloy wherever possible: the stringent specifications and the cost of achieving them in the first place can justify them having their own closed loops: production of a specific alloy, its use phase and then collecting and recycling that alloy material to produce new material that matches the original specification. The motivation is economic. If the identity of the alloy can be maintained from fabrication to the end-of-life of the component, the alloy producer can use that scrap alloy to make new alloy components. This is economically and environmentally efficient as it allows the producer to achieve high-quality product specifications without incurring extra refining or qualification costs [30]. Nickel is usually recycled and a distinction is often made between the use of newly produced metal and recycled scrap. By far, the most important use of new nickel is the production of stainless steel. This use accounts for close to two thirds of first-use nickel and has increased considerably over the past few decades. The market for stainless steel is growing at the rate of about 5% per annum. Other sectors of the first use include other alloyed steels, high nickel alloys, castings, electroplating, catalysts, chemicals and batteries. The percentages are depicted in Figure 2 [4]. 3

12 Figure 2 Nickel Resources [4]. The thesis involves the design and implementation of a solution for slag skimming in nickel production from a cabin away from the converting vessel (remote location). The main purpose of the project is to study how thermal imaging can be deployed in the process and how the data provided by thermal imaging can be used to improve the quality of the skimming process while maintaining high safety and health standards for skimming operators. Skimming means the process of pouring the slag out of the converting vessel and limiting the wastage of processed nickel. A thermal camera focuses straight into the stream coming out of the vessel and provides live readings of the slag versus matte percentage, which helps the skimming operator to take a call on when to stop pouring or adjust the pouring speed. The system consisting of multiple cameras and visuals has been designed such that it is easy to use and is operator friendly as well as scalable and configurable to allow for varying grades of the nickel ore sourced from different suppliers. Nickel cleanness is an important factor in the economic production of nickel and the quantity of slag carried over from one process to the next is a significant 4

13 parameter. The financial implications of the slag carried over are serious, whether it occurs intermittently or routinely for any given process. The additional costs have to be borne by the manufacturer and by the downstream processes and include the following: Nickel Plant Costs: Reduced alloy recovery, Increased additional costs, and Incapacity to produce nickel at desired specifications. Downstream costs: Increased use of time and materials in secondary nickel-making processes, Increased plant maintenance downtime, Increase in nonmetallic inclusions in cast products, and Increased site safety. 5

14 CHAPTER 2. BACKGROUND AND THE PROBLEM At Kalgoorlie Nickel Smelter, there are three converters and two of them are used simultaneously in the converting area. The converting process begins with the movement of nickel matte from the furnace to the converters. Matte is tapped from the furnace into pots, which is then transferred across to the converters via two overhead aisle cranes. Once the converter has been initially charged, it begins the process of oxidizing the iron and iron sulfides in matte to produce slag, which is then skimmed off to increase the nickel grade. This process is known colloquially as skimming. When slag is skimmed off the top, the converter is subsequently topped with additional pots of nickel matte. Once the converter receives tons (only tons of Flash Furnace Matte [FFM]) of high-grade nickel matte, it is emptied pot by pot via the overhead aisle cranes to the matte granulation system. The whole process of nickel processing is depicted in Figure 3. Figure 3 Nickel Smelting Process Flow Diagram. 6

15 The thesis is mainly concerned with the area circled in RED in the Figure 3 above and the numbered areas are defined as follows: 1. Flash furnace; 2. Slag pots filled at furnace s slag end to be dumped at the waste site; 3. Matte pots filled to be processed by the converters (4) and then brought back from converters for reprocessing; 4. Converter; 5. Granulator processing the converter s processed product to producenickel granules; and 6. Crane aisle highlighted with the RED arrow. At the smelter, there are three converters each with its own skimming cabin in the crane aisle. The furnace processes the ore and prepares a product with about 45% nickel in there, which is then poured into converters via pots transferred by the crane. The whole process is scheduled via the crane aisle scheduling program and following a shift plane for the converters based on a number of factors. The crane (#6) is used to transfer the product from one place to another such as the furnace (#1), converter (#4) and granulator (#5) using specifically designed pots (#3). Converting is a type of metallurgical smelting that involves several processes; the most commercially important form is the treatment of molten metal sulfides to produce crude metal and slag, as in the case of nickel converting. The main aim of this converting process is to reduce the amount of nickel carried in the slag and to reduce the reprocessing of the product, which wastes time and has a financial impact on the business. Currently, the whole skimming process is manual and relies on personnel judgment based on various calculations to take a call for the amount of slag 7

16 being skimmed and the total processing time. There have been numerous times when either the processing time is too long or too short resulting in either a lot of wastage or reprocessing of nickel matte. The current skimming cabin is located next to the converter and inside crane aisle that exposes skimming operators to dangerous situations as below: Close proximity to cranes with pots full of slag/matte Heat Molten metal SO 2 (sulfur dioxide) fumes Dust Excessive noise The operator looks through a glass window as seen in Figure 4 below at the converter mouth to assess the color difference between the slag and matte, and this has been the manual process for decades. Currently, the operators use the required personal protective equipment (PPE) to reduce exposure to avoidable hazards and they get out of the skimming cabins while the cranes transfer molten material in the converting vessel or across the aisle to the furnace. This process is quite time-consuming. 8

17 The Converters and the cabins are as shown below: Figure 4 Converter View from Across the Aisle and Inside of Existing Skimming Cabin. This manual skimming process is quite dangerous due to the various factors mentioned above, plus the molten metal splashes from the converter itself that has the potential to shatter the glass in the door as below: 9

18 Figure 5 The Existing Cabin s Door with Shattered Glass Window. The Tinted Glass used as Visual Assistance while Skimming. By studying the above situation, it is quite evident that the skimming operators perform their job in quite a hazardous and dangerous environment, which should not be the case as technology can make a difference and improve the situation. This situation has created an opportunity to look into possible less-dangerous converter slag skimming solutions, and that is the main goal of this thesis. Why Slag Detection is Essential Current System in Use There are a few methods used in the worldwide nickel industry, but the Kalgoorlie Nickel smelter uses just the following: Visual Inspection without any technical aids: During the skimming process, operators view the skimming stream from a convenient position that may be above, 10

19 below or from the sides to observe the transition into slag as an increase in brightness. Depending on the process, additions to the melt can take place, producing vast amounts of airborne dust, smoke and gases. During the process of visual inspection of skimming stream, it is extremely difficult to distinguish between the two products matte and slag, thus the process is highly susceptible to the operator s skill variances. Figure 6 Slag Pot View Using an IP Camera. Another very important issue concerning the operators is their safety, which can be addressed by minimizing their exposure to the molten metal and the associated problems, thus reducing site-related accidents. The technique discussed above to control the carry-over of slag from one process to another is not totally reliable for the reasons discussed hereinbefore; this has led to the introduction and requirement of a new technology to replace or complement the current system, a cost-effective thermal imaging system will lead the way forward [5]. 11

20 2.1 Emissivity Emissivity represents any material s ability to emit thermal radiation and is an optical property of the matter [11]. The emitted energy indicates the temperature of the object. Emissivity can have values from 0 (shiny mirror) to 1.0 (blackbody). Most organic, painted, or oxidized surfaces have emissivity values close to A majority of thermal (Infrared) camera sensors have adjustable emissivity feature to ensure accuracy when measuring other materials such as shiny metals [12]. Every object the temperature of which is above zero kelvin ( C) emits radiation. The emission is in the form of heat and is dependent on the temperature. The wavelength of the majority of this radiation lie in the electromagnetic spectrum above the visible red light as seen in Figure 7, in the infrared domain. Infrared radiation transports energy, and this radiated energy is used in determining the temperature of the object being measured. The phenomenon is similar to that of a radio antenna, where one transmits and the other receives the signals and transform them into electric signals [12]. Figure 7 Electromagnetic Spectrum [13]. 12

21 The emission coefficient ε is the relationship of the emission output of an object to the emission output of a black body radiation source at the same temperature. ε is influenced by the object s material and changes with the wavelength, the temperature or other physical values. As already described, the emission coefficient ε of an object is the most important value when determining its temperature with a pyrometer. If one wants to measure the actual surface temperature of an object with a pyrometer, one must know the emission coefficient, or emissivity, of the object and enter its value in the pyrometric measuring system. To adjust for the material being measured, pyrometers therefore have an emissivity setting. The values for the various materials may be taken from Table 6). In principle, the emissivity of a material is influenced by wavelength, temperature, etc. Because the emissivity is dependent on wavelength most materials can be grouped as follows: 1. Metals 2. Nonmetals 3. Transparent materials (opaque) The emissivity of smooth metal surfaces is high at short wavelengths and decreases with lengthening wavelengths. With oxidized and soiled metal surfaces results are not consistent; emissivity may be strongly influenced by temperature and/or wavelength. The emissivity of metals also changes with time due to wear and tear, oxidation or soiling. Pieces of metal are often smooth after processing and their 13

22 surfaces are changed by heat. Discoloration occurs and can be followed by rusting and scaling. All this can change the emissivity and must be considered to avoid errors. However, so long as surfaces are not shiny, metals can be measured well in most cases. 2.2 Thermal Imaging Infrared thermography (IRT), thermal imaging, and thermal video are examples of infrared imaging science. Thermographic cameras usually detect radiation in the long-infrared range of the electromagnetic spectrum (roughly 9,000 14,000 nanometers or 9 14 µm) and produce images of that radiation called thermograms. Because infrared radiation is emitted by all objects with a temperature above absolute zero according to the black body radiation law, thermography makes it possible to see one s environment with or without visible illumination. The amount of radiation emitted by an object increases with temperature; therefore, thermography allows one to see variations in temperature. When viewed through a thermal imaging camera, warm objects stand out well against cooler backgrounds; humans and other warm-blooded animals become easily visible against the environment, day or night. As a result, thermography is particularly useful to the military and other users of surveillance cameras [11]. Thermal imaging cameras cannot detect the emissivity of objects to calculate their true temperature. They can only calculate the apparent temperature of the objects. The apparent temperature of an object is a function of both its temperature and emissivity. Given two objects with the same true temperature but different emissivities, a higher apparent temperature is calculated for the object with a higher emissivity as seen in Figure 8. 14

23 Figure 8 Emissivity Explanation [14]. Given two objects with the same emissivities but different actual temperatures, a higher apparent temperature is calculated for the object with a higher actual temperature. The apparent temperature of an object may be substantially different from its actual temperature. Only when the emissivity of objects is known can thermal imagers compensate for emissivity and calculate the actual temperature [14]. 2.3 Characteristics of Infrared Infrared is invisible because its wavelength is longer than that of the visible light. It has nothing to do with brightness or darkness of the visible light. Any object with an absolute temperature of zero kelvin (0 k) or higher emits infrared. Therefore, it can be applied to any field. It has a characteristic of heating an object. Therefore, it is sometimes called the heat wave. It is a kind of light (electromagnetic wave). It can be transmitted through vacuum as well. There is a correlation between infrared energy and temperature of an object. Therefore, it can be used to measure the temperature of an object [19]. 15

24 2.4 How the heat transfers Emission: A type of heat transfer where the heat is transferred directly from the surface of an object as an infrared energy. Convection: A type of heat transfer where the heat is transferred by the heated part of gas or liquid moving upward. Conduction: A type of heat transfer mainly through a solid object. Figure 9 Heat Transfer [19]. 2.5 Emission, reflection and transmission of infrared An object that absorbs infrared well emits infrared well (Figure 10). 16

25 Figure 10 Emission vs Reflection vs Transmission [19]. 2.6 Principle of measurement by Infrared Thermography equipment Infrared thermal camera works as per the principle displayed in Figure 11: Figure 11 Infrared Thermography [19]. The thermal camera detects infrared waves (heat) emitted from the object. The energy of infrared waves is transformed into temperature (electronic signals). The temperature signature is displayed as an image. 17

26 CHAPTER 3. LITERATURE/PREVIOUS RELATED WORK Thermal Imaging is quite an important topic and has been researched quite extensively. The thermal imaging technology for skimming was discussed in a paper titled Multispectral system for measuring the radiation parameters of steel slag during the discharge of steelworks furnace presented during the 11th International conference on Quantitative Infrared Thermography [6]. The paper in [6] discussed the development of a multispectral system for measuring and calculating the chosen radiation parameters of the steel slag for the investigation of FeO content. The system contains two infrared (IR) and two visual (CCD) cameras. IR cameras capture images in MWIR and LWIR spectral ranges. 3.1 Technology Introduction The chemical content of the steel slag is very important technological parameter during steel production. The concentration of FeO together with the basicity of the slag is the basic figure that allows estimating the steel and slag qualities. Typically, the content of FeO is now measured off-line by chemical and spectrophotometric analyses. It requires stable and repetitive measurement conditions and is a time-consuming procedure using the complex mathematical and chemical modeling. Recently, the IR thermography has been introduced in steel mills. It is now used to estimate the moment of slag appearance that gives an automatic signal to stop discharging the vat. It is relatively simple, as the emissivities of steel and slag differ significantly [3]. Now, there is a hope to extend the thermography applications in steel production to online estimation of the FeO content in the steel slag by analyzing the 18

27 visual and infrared images during the pouring out of the vat. The results of the initial investigations confirm the possibility of using the multispectral system operating in visual and infrared spectra starting from 0.5 μm up to 14 μm [3]. 3.2 Research Paper s Results During the preliminary measurements, high difference in the values of some parameters for steel and slag were noted. Besides the mean temperature and emissivity that are different for steel and slag, the temperature decay along the stream significantly varies. Low varying temperature characterizes the slag (Figure 12); for the steel the fluctuation of temperature is much higher. A similar conclusion can be drawn while calculating the standard deviation of temperature in the region of interest as presented in the table in Figure 12a. Note that in the table, all values of temperature are apparent temperatures (we call them radiation temperatures), and they were obtained using the default value of emissivity. ε=0.95. The table in Figure 12a shows exemplary values of chosen parameters for mid-wavelength infrared (MWIR) and long-wavelength infrared (LWIR) thermal images, reference temperature obtained by contact measurement T = 1662 C [7]. 19

28 Figure 12a Temperature Trends for MWIR Thermal Images for Both Steel and Slag. b) Figure 12b Temperature Trends for MWIR Thermal Images for Slag (Detailed View) (results from an earlier study [7]). By considering the results and the discussion hereinbefore on the processes involved in the steel industry, it is evident that thermal imaging would be helpful for slag skimming in nickel manufacturing and the solution can be implemented successfully. After passing on the experimental results and the working methodology from the smelter to the camera manufacturer, we received a positive feedback, and a thermal camera was provided on a loan for slag skimming trial. 20

29 CHAPTER 4. METHODOLOGY AND THERMAL CAMERA TRIAL Liquid matte (nickel) and slag have different emissivities and therefore radiate at different rates when at the same temperature. Slag has a high emissivity due to the high number of good emitters within its composition, whereas matte has a low emissivity. The difference in emissivities between matte and slag changes across the infrared spectrum, with the difference between the two being greater at longer wavelengths. A thermal image of the stream displayed in the remote location enables the operators to recognize a change in the brightness easily and detect when matte begins to pour. It is possible to use different colors for slag and for matte in the display and to provide an alarm signal when matte is detected above the alarm threshold. Liquid matte and slag have approximately the same temperature during tapping, though plant operators believe that slag is actually hotter. Then, in this case the apparent temperature difference will be enhanced making the distinction between the two even clearer. During the remote slag skimming trial, the thermal camera was set up to focus at the converter s mouth where the material is poured into pots and the visual from it was captured by an IP camera that was set up inside the cabin as displayed in Figure 3. The skimming operators watched the visuals as well as conducted physical inspection of the stream to confirm the camera findings about slag versus matte percentages. This set-up was trialed for 6 weeks and the experimental results confirmed the camera findings about nickel percentage in slag pots. The findings 21

30 provided sufficient evidence to support the case of slag skimming from a remote cabin, which is away from the crane aisle and converting vessel. During the trial, the following images were obtained from the thermal camera and the graph below shows the percentage of slag in BLUE, while matte is displayed in GREEN. The difference in the thermal image from a stream of matte to one of slag is clearly visible from the figure below; the matte is indicated by green streaks [5]. 4.1 Thermal Camera Visual The main objective of the thermal camera is to assist in identifying the presence of matte while pouring slag out of the converting vessel. Following is a screenshot of the thermal camera visual displaying matte during the skimming process as in Figure 13. It is generally believed that matte has a lower apparent temperature than that of slag, which helps the camera spot it within the slag stream. Figure 13 Thermal Camera Image. 22

31 Point 1 in Figure 13 is at 841 C surrounded by slag at significantly higher temperatures. The matte is displayed in the temperature range C and the slag is at a higher temperature. Following are few graphs showing the percentages of matte versus slag as displayed on thermal camera s visual: SLAG % MATTE % Figure 14 Skim 1 in the Blow. The pie chart on left hand side of Figure 14 above shows 12.4% matte and 87.6% slag in this particular skim. The line graph on the right side shows the running percentages of matte versus slag for duration of the skim. This is the first skim during the cycle and has a high percentage of slag, thus it will be sent back to furnace for reprocessing. 23

32 Figure 15 Matte and Slag Percentages Displayed in the Bar Graph and Temperature Color Palette with the Temperature Range on the Top Right Side. Figure 15 is a screenshot of the thermal camera visual that displays a skim in progress, whereas Figure 14 displays the live results of slag versus matte percentages as the camera focuses into the liquid stream being poured out of the converter into the pot. Thermal camera software displays a running percentage of matte versus slag as seen in Figure 16 below, which is taken from the second skim as the percentage of slag decreases in comparison with skim 1 displayed in Figure 14 above. A live comparison graph helps operators to take a call as to when to stop or slow down. 24

33 SLAG % MATTE % Figure 16 Skim 3 in the Blow. The pie chart on the left hand side of Figure 16 given above shows 36.8% matte and 63.2% slag in this particular skim. The line graph on the right side shows the running percentage of matte versus slag for duration of the skim. This is the third skim during the blow and still has a high percentage of slag, thus it will be sent back to the furnace for reprocessing. SLAG % MATTE% Figure 17 Skim 4 (High Grade or FINAL) in the Blow. The pie chart on left hand side of Figure 17 above shows 76.3% matte and 23.7% slag in this particular skim. The line graph on the right side shows the running percentage of matte versus slag for duration of the skim. This is the fourth skim 25

34 during the cycle and has considerably low percentage of slag. This pot will go for granulation to be processed and converted into the final product of nickel granules. The screen shot of the thermal camera screen below (Figure 18) was taken during a high-grade skim where most of the slag has already been skimmed and what is left is the final product with a high percentage of nickel which will be granulated to get to the end result of nickel granules. Figure 18 Skim 5 (High Grade or FINAL) in the Blow This Pot goes for Granulation. The steps to implement the system of remote slag skimming using thermal and IP cameras are as follows: 4.2 Proposed Solution: Remote Skimming Existing cabin to be relocated to a different place and all the controls to be extended to operate the equipment remotely; Current HMI (Citect) to be improved further; 26

35 Safety interlocks to be improved for fail safe state; IP Cameras to be utilized to monitor the converter, cranes and pots; Thermal imaging camera to be utilized to monitor the product inside the converter and also the percentage of matte/slag while skimming from the converter; and Training materials to be revised to suit remote monitoring and skimming. The main steps for achieving the desired outcome of the thesis can be divided into three sections as given below: Remote Cabin Setup Extend the pneumatic drive controls to the new cabin; Install solenoids to control the mechanical drive/equipment in the existing cabin; Install new PLC to control the new equipment and make it safer; Install and configure a new SCADA terminal; and Install display screens for the cameras Improved Network Setup Fiber and copper network extension New high-speed network switches High-quality IP camera: Pelco (manufacturer), Model: Sarix IP 2MP High Temperature range Thermal camera selection: Pelco, 27

36 4.2.3 Camera Hardware and Installation A blower to cool down camera jackets as the environment is quite hazardous and has exposure to high temperatures Suitable brackets for all the cameras Three displays for Thermal and IP cameras (HP screens 40 inch and 2 24 inch) New HMI screens 28

37 CHAPTER 5. EXPERIMENTATIONS The thesis implementation will ensure that all the data are collected and compared with those of the lab assays. A sample image of the experimental data results from the lab is shown below, which shows the percentage of nickel (matte) in the tested pots in column 6 of Figure 19A. The information in columns 3, 4 and 5 is quite self-explanatory and #3 mentions the skim number in a particular blow given in column 4, whereas #5 states the number of the converter. The rest of the columns from #7 to #13 display the amount of other impurities in the pots. The HMI screens as displayed below will have access to historical data and samples taken from the current blows to make informed decisions. Figure 19A Converter Slag Samples An Extract from Lab Report. 29

38 Figure 19B Converter Slag Samples Screenshot from the HMI Screen. The data comparison in Figures 19A and 19B with the matte slag percentages provided by the thermal camera such as those in Figures 14, 16 and 17 ensures we can improve the quality of the system and reduce the matte carryover, which will increase the profit margin for the company as well. The main benefits of the system are as listed below: An automatic indication of the presence of matte in the slag stream; Real-time signal output in the control room; Reliable alarm independent of the operator; Reduced additions and rework costs; Matte detection images can be recorded for later analysis and process improvements; Installation requires minimal alteration to the existing set-up; Noncontact measurement; 30

39 Improved performance; Overall nickel plant performance and profitability is increased; and Improved work conditions for skimming operators. 31

40 CHAPTER 6. NETWORK DESIGN/HARDWARE INSTALLATION AND FUTURE WORK The camera network has been implemented in a way as shown in appendix A, where all the controls from the existing converter 3 cabin have been extended to the remote cabin and all the necessary cameras have also been brought back to the remote cabin via a 1 Gigabyte backbone. The camera screens have been mounted on three separate brackets, one for the thermal camera and two for IP cameras, as displayed in Figures 20 and 21: Figure 20 Camera Screens in Skimming Cabin. 32

41 Figure 21 Camera Mount View from Across the Converter Aisle. Figure 22 Thermal and IP Camera Mount View from the Skimming Platform. 33

42 The future work may involve automating the whole skimming process and may not need an operator in the area, which means reduction of workforce and less variability of the process and improved quality of the product. 34

43 CHAPTER 7. RESULTS This thesis is meant to add a potential value to the nickel converting process and skimming operations as a decision support tool to aid operators in navigating the multivariate considerations that are required to skim the required amount of slag optimally. The future work will be focused on extending the current set-up to a larger scope including increased number of converters and additional operating tasks such as automating the whole skimming operation. The combination of IP and thermal cameras make it possible to skim from a remote location without having any effect on the final product. It has been proven during the remote skimming trial that the desired results can be obtained by utilizing the combination of IP and thermal cameras. The raw data achieved during the trial from skims with and without camera are given in Appendix E. Trial Duration = 6 weeks Number of blows with camera and without camera = 35 Average percentage of nickel in skims, without camera = 3.06 and with camera = 2.99 Standard deviation without camera = 1.94 and with camera = 1.08 The trial results are displayed in the following charts: **The vertical axis represents average nickel percentage in skims and the horizontal axis represents time. 35

44 1/11/2016 0:00 3/11/2016 0:00 5/11/2016 0:00 7/11/2016 0:00 9/11/2016 0:00 11/11/2016 0:00 13/11/2016 0:00 15/11/2016 0:00 17/11/2016 0:00 19/11/2016 0:00 21/11/2016 0:00 23/11/2016 0:00 25/11/2016 0:00 27/11/2016 0:00 29/11/2016 0:00 1/12/2016 0:00 3/12/2016 0:00 5/12/2016 0:00 7/12/2016 0:00 9/12/2016 0:00 11/12/2016 0: Average Nickel % Skimming Without Camera 3.06% Figure 23 Average Nickel Percentage in Skimmed Slag Without Camera Average Nickel % Skimming With Camera 2.99% Figure 24 Average Nickel Percentage in Skimmed Slag With Camera. From the charts in Figures 23 and 24, it is evident that we have reduced the amount of nickel percentage, and the variance of nickel percentage in skims has 36

45 dropped significantly as proven by the standard deviation values (1.08 vs 1.94), which is a terrific result. The summary of the results of this study are as below: Improved safety of the operators o The combination of the cameras trial has proven that skimming operation can be managed from a remote location at a safe distance from the converter and away from the crane aisle. Consistent quality of the product and standardized operation for converter skimming o Thermal imaging camera is utilized to assist operators with skimming the slag and taking the calls to Roll In or Roll Out the converter based on the percentage of matte in the slag pots. o The quality control includes a comparison of the nickel versus slag percentages reported by the thermal camera with the values supplied from the onsite lab from live samples. o All the operators use the same technique to perform the skimming, which has standardized the skimming operation. Reduced stress levels for the staff in skimming cabins This is proven by the Perceived Stress Test, which researchers use the most to measure stress [25]. 37

46 A survey of 10 questions explored the operators thoughts, feelings, and reactions during and before the trial month. The survey was conducted on 5 operators before and after the trial and the findings are tabulated below: Converter Slag Skimming from Remote Cabin Perceived Stress Test Scores Operator Before Trial After Trial Average Score Legend Scores of 13 are considered average or low stress. Scores between 14 and 19 indicate moderate stress. Scores of 20 are considered high stress. Figure 25 Perceived Stress Test Results. The results are represented in Figure 26 below in a chart form for easier understanding and the raw data are given in Appendix D. 38

47 Figure 26 Perceived Stress Test Result s Chart. It is evident from the results that the perceived stress level has gone down considerably after operators have been performing slag skimming from the remote cabin. Reduced delays on Converter 3 when slag is being returned This is achieved because the operator skims from a remote location and does not have to get out of the cabin to allow the cranes pour matte in the launders to the furnace. This step of getting out of the cabin was necessary for the operator s safety and it accumulatively wasted around 2 hours in a 24 hours operation. 39

48 CHAPTER 8. CONCLUSION The main objective of this thesis was to prove the concept of remote slag skimming utilizing high-end thermal camera and a combination of IP cameras. This method of slag skimming has not been tried in the nickel industry as yet, making it the first of its kind. A remote skimming trial spanning over 6 weeks was run without compromising the product quality. During the trial the percentage of nickel in slag dropped, which meant less wastage, and the skimming process improved due to thermal camera s data analysis and close temperature monitoring of the matte or slag stream coming of the converting vessel. The setup of cameras and the remote location of the cabin reduce the total blow times as operators do not need to step out of the cabin for crane movements, making the system more efficient and effective. The skimming operators have visuals of the entire converting area and access to the live data analysis provided by the thermal camera software, which have enabled the operators to do their job effectively from a location away from the converting vessel and the crane aisle. This remote location skimming is a huge improvement for operator s safety and indirectly reduces the operator s stress level, which is another desired outcome. The data analysis of the trial results given in Section 7 proves the fact that the camera setup carried out for the thesis has improved the operators safety, has increased the product quality without any compromise., has reduced the operator s stress level, and above all has made the slag skimming process less time-consuming and more efficient. 40

49 The successful implementation of the system and the trial has paved the way for future installation of a similar setup for the rest of the converters at the smelter and also set us on a journey to enhance the system as well as improve the product quality while ensuring a safe, effective and efficient nickel slag skimming process utilizing thermal and IP cameras. 41

50 CHAPTER 9. APPENDIX 9.1 Network Layout 42

51 9.2 Stress Level Test Perceived Stress Test Ten questions explore your thoughts, feelings and reactions during the last month. Double-check to ensure you have answered all the 10 items. When you have completed the test, please drop it in the box provided. The test is anonymous and no data are retained by the company. 1. How often have you been upset because of something that happened unexpectedly? Never Almost Never Sometimes Fairly Often Very Often 2. How often have you felt that you were unable to control the important things in your life? Never Almost Never Sometimes Fairly Often Very Often 3. How often have you felt nervous and stressed? Never Almost Never Sometimes Fairly Often Very Often 43

52 4. How often have you felt confident about your ability to handle your work problems? Never Almost Never Sometimes Fairly Often Very Often 5. How often have you felt that things were going as planned? Never Almost Never Sometimes Fairly Often Very Often 6. How often have you found that you could not cope with all the things that you had to do? Never Almost Never Sometimes Fairly Often Very Often 7. How often have you been able to control irritations during your work hours? Never Almost Never Sometimes Fairly Often Very Often 44

53 8. How often have you felt that you were on top of things? Never Almost Never Sometimes Fairly Often Very Often 9. How often have you been angered because of things that were outside of your control? Never Almost Never Sometimes Fairly Often Very Often 10. How often have you felt unsafe during the course of performing your duties? Never Almost Never Sometimes Fairly Often Very Often 45

54 9.3 Thermal Camera Setup Screens 46

55 9.4 Perceived stress test sheets Operator 1 before the camera trial 47

56 Operator 2 before the camera trial 48

57 Operator 3 before the camera trial 49

58 Operator 4 before the camera trial 50

59 Operator 5 before the camera trial 51

60 Operator 1 after the camera trial 52

61 Operator 2 after the camera trial 53

62 Operator 3 after the camera trial 54

63 Operator 4 after the camera trial 55

64 Operator 5 after the camera trial 56

65 9.5 Thermal Camera Trial Raw Data Skims without camera Raw Data Skim Date Time & Skim Type Converter# Skim Blow# AV_Ni % Without Camera AV_Cu AV_Co AV_Fe AV_Al2O3 AV_MgO AV_SiO2 AV_CaO AV_S AV_Fe3O4 1/11/ :00 CVS /11/ :41 CVS /11/2016 1:40 CVS /11/2016 0:08 CVS /11/2016 2:00 CVS /11/2016 7:21 CVS /11/2016 0:05 CVS

66 8/11/2016 8:00 CVS /11/ :50 CVS /11/ :45 CVS /11/ :50 CVS /11/ :50 CVS /11/ :00 CVS /11/ :45 CVS /11/ :30 CVS /11/2016 1:47 CVS /11/2016 2:00 CVS

67 19/11/2016 5:38 CVS /11/ :12 CVS /11/ :20 CVS /11/2016 0:50 CVS /11/2016 8:06 CVS /11/ :00 CVS /11/ :30 CVS /11/ :50 CVS /11/ :10 CVS /11/2016 6:44 CVS

68 29/11/2016 2:40 CVS /11/2016 4:10 CVS /12/2016 9:09 CVS /12/ :30 CVS /12/2016 5:50 CVS /12/2016 6:30 CVS /12/ :30 CVS /12/ :53 CVS

69 9.5.2 Skims with camera Raw Data Skim Date Time & Skim Type Converter# Skim Blow# AV_Ni % With Camera AV_Cu AV_Co AV_Fe AV_Al2O3 AV_MgO AV_SiO2 AV_CaO AV_S AV_Fe3O4 12/12/ :19 CVS /12/2016 4:05 CVS /12/2016 3:31 CVS /12/2016 1:12 CVS /12/2016 9:25 CVS /12/2016 8:00 CVS /12/2016 7:20 CVS /12/ :47 CVS

70 4/12/ :02 CVS /12/ :06 CVS /12/2016 2:00 CVS /11/2016 0:25 CVS /11/2016 7:04 CVS /11/2016 6:19 CVS /11/ :44 CVS /11/2016 3:15 CVS /11/2016 2:10 CVS /11/ :52 CVS

71 19/11/ :43 CVS /11/ :00 CVS /11/ :45 CVS /11/ :25 CVS /11/2016 3:15 CVS /11/2016 2:10 CVS /11/ :30 CVS /11/ :36 CVS /11/ :45 CVS /11/ :42 CVS