Mechatronics Exercises EDGE

Transcription

1 1 Mechatronics Exercises EDGE Prof: Panu Kiviluoma Spring 2015 Aalto University By: Oriol Ala Puig Bijan Bayat Mokhtari Jonas Eklöf Hyunsoo Kim Pontus Salminen

2 Table of Contents 1 Introduction Brainstorming Screening Concept Selection Product Development Team roles Schedule Budget Design space exploration Benchmarking Related Technology Scoping Product characteristics Concept design and prototyping Concept generation Evaluation Selection Prototyping ELECTRONICS PROGRAMMING Reading sensors Web UI Executing Actions Actuation CASE Product and Process validation Testing and validation Technical documentation PRODUCTION AND MATERIAL COSTS Mold and part cost for the plastic parts Formulas used for estimating the mold costs Formulas used for estimating the part costs Summary of mold and part costs Electronics costs Summary References

3 1 Introduction This is the report of the process, procedures, learnings, and final result of Mechatronics Exercises course project. The team created an IoT sensor package aimed for home use called EDGE. This project was also submitted to the Interdisciplinary Product Development (IPD) course. 1.1 Brainstorming First step after team formation, before selecting team leader and delegating tasks, was to decide on a product that the team would develop. Since this project was shared between the IPD course and the Mechatronics Exercises course, the product had to have a mechatronic nature while still satisfying the needs of product development course. The team chose the brainstorming method for project selection, since it was the most familiar for team members and was suitable for generating a large number of ideas, and decided that the members should first ideate about projects individually. At the brainstorming session the members took turns on writing the ideas which they had come up with on the board and presenting them to the team. At this point the ideas were not criticized and they were only discussed and clarified by the presenter. The ideas were only renamed if the original name was not clear enough. After individual presentation of ideas, the team ideated collectively to generate new ideas or make variations of the original. 1.2 Screening Once a large number of ideas were generated, the team set on to screen through them based on feasibility, complexity, how it satisfied the requirements for the courses, and possible marketability. At this point the team members asked the presenter of the idea to explain more about the idea and then the idea was criticized by the team members. A list of pros and cons were made for each idea. The owner of the idea was given the chance to eliminate any of the ideas that they didn t like before the final elimination. After this, each person chose the top five ideas that they liked best and the rest were scrapped. The final idea was selected by the Weighted Decision-Matrix method Concept Selection To eliminate bias towards ideas and to objectify the concept selection the Weighted Decision-Matrix method was used. In this method the top seven ideas were listed on the vertical axis of a table and the criteria on which they would be judged upon on the horizontal. Then each criteria was given a weight between 1 to 5, 1 being the least important and 5 being the most important. Next each concept was given a score between 1 and 10 based on how well that concept did on that criteria. The scores were an average of the scores that each individual suggested. Scores were then multiplied by their weights and summed. The concept with the highest score was chosen as the project. The matrix can be seen in Table 1. 3

4 Table 1: Weighted Decision-Matrix Cost Ease of manu. Innovation Ease of coding IPD friendly Mech. friendly Total Weight (1-5) VR Game Cart Follower IoT Sensor Snow Plow Snow-Skate Drive by Mass Gimbal Figure 1: Team member, Oriol Ala Puig, explains his ideas. 4

5 2 Product Development 2.1 Team roles The first roles to be decided were team managers. As the project is a part of two courses, two managers were to be elected one for each course part. The leaders were chosen with election. For mechatronics Bijan Bayat Mokhtari and for IPD Max Johansson were elected as managers. As the project was large and consisted of many different elements the project was divided into several tasks. Each team member was assigned with one or several tasks to be responsible for. The tasks were divided with a discussion where personal preferences were taken into account. The roles were divides as such: 2.2 Schedule The schedule was decided in the third meeting. As the project was ambitious in its scale, the time dedicated for individual segments of the work was kept very limited in order for the product to be deliverable for the given deadline. The schedule can be seen in figure 2. Table 2: Team roles Mechatronics Leader IPD Leader Mechanical Design Electronics Design Documentation M Documentation IPD Web Programmer Secretary / Organizer Procurement Business Bijan Max Oriol Pontus Bijan Max Hyunsoo Jonas All Max Oriol Figure 2: Schedule 2.3 Budget The project didn't have a specific budget but the price of device must be kept low enough to be appealing for consumer. For BOM and component cost navigate to table Design space exploration Different alternatives upon the idea and functionality of the IoT sensor were considered for the design space exploration. This made it possible for the whole team to, as a group, work together on the perception of the IoT sensor and therefore set some limitations. Questions asked for the use of the IoT 5

6 sensor were if it should be used indoors/outdoors or both. When decided upon the functionality of the sensors, considerations regarding what sensors would be needed for the different functionalities to work. A number of sensors were listed whereas they were decided to be included or not. The agreement on what to be included or not depended on different observations like programming level difficulty, implementing with other sensors and finally the price of the sensor. Table 3 represent the sensors that were considered for the IoT sensor and the final decision made. Table 3: Design space exploration of the sensors, final decision to include and comments. Sensor Include Comment Accelerometer yes Easy to program, many functionalities and cheap Magnetometer yes Easy to program and cheap Gyro yes Easy to program and cheap Barometer maybe Too difficult to implement Light yes Easy to program, simple, cheap Sound maybe Simple functionality, cheap Camera no Too difficult to program Movement/Proximity yes Cheap, simple and easy to program GPS maybe Expensive, difficult to program and implement Temperature yes Simple, easy to program and cheap Humidity maybe Simple, easy and cheap Gas sensor no Too difficult to program Out of all different types of sensors 8 were finally chosen to be focused on. Based on the list of sensors chosen, a shopping list was prepared for prototyping. 6

7 2.4.1 Benchmarking A comparison with the existing market of similar products were made to know what sensors were used, other components it included, and different features. Also the up time in how long the battery would last, price, and finally special features. All products included accelerometer and temperature sensor. Other sensors depended on the product and the main use for the product. Sense Mother is a device used to monitor the environment indoors and outdoors. The Sense Mother includes 4 different cookies that include an accelerometer and temperature. Sense Mother is connects to a smartphone through Bluetooth and with the user friendly UI can easily manage the Cookies (small sensor units). One special thing with Mother Sense is the hub, which is the Mother that is the connection between the Cookies and the internet. Sense Mother has a long battery life up to 1 year. The price for Sense Mother is high but includes 4 products in one with a simple and friendly UI. Thingsee has a variety of many different sensors. Since Thingsee was found from a recently successfully crowd funded project, it was not easy to find any detail information about the product. Impressive features for the Thingsee is that it has GPS for outdoor use, Wi-Fi, 3G/4G, and waterproof capabilities. The product is mostly used for people familiar with programming skills to decide exactly how the sensors should be used. Thingsee is independent which means it does not require a hub. The up time were also long but had a price that was almost similar to the Sense Mother. Knut is a combined sensor hub which enables the user to monitor the environment indoor and outdoor. It is connected through Wi-Fi and is powered with normal AA batteries. Special feature with Knut is that it is small and expandable which means that any sensor can be added to the sensor hub. Knut also requires some programming skills and does not provide with much detail since it was a successfully crowd funded project like the Thingsee. Figure 3: Benchmark of the most fundamental competitive products Related Technology The team listed advantages and disadvantages for The Mother Sense, Thingsee and Knut. With this the team decided on what should at least be included and what to avoid. The goal was to combine all the pros of the different products into one which would result in the IoT sensor. 7

8 Table 4: Advantages (green) and disadvantages (red) of the different products Mother Sense Thingsee Knut Easy to use / intuitive Functionalities Open attractive / well designed indoors & outdoors expandable, used with any sensor Good price/sensor independent low initial cost UI rugged normal AA batteries Expandable open csv data export open good battery needs purchase of each sensor Dependent expensive ugly Ethernet cable unintuitive unintuitive only indoors big uses AA batteries initial cost high Only one? N/A Scoping The result from the space exploration and the research of currently existing products were to make a consumer friendly IoT sensor that would be user friendly. The IoT sensor should be inexpensive in order to be more attractive than current products and open source for people to have the opportunity to modify it. The IoT sensor should also come with a hub that would have the possibility to work as a charging station and also the possibility to connect multiple IoT sensors to it. 2.5 Product characteristics Based on competitors concepts of IoT sensor bundles, the EDGE concept was designed and developed. This new device consists of three plastic parts: main body, top and bottom. It has 8 main sensors (accelerometer, gyroscope, magnetometer, sound, temperature, humidity, light and motion) an RGB LED, vibration motor, micro controller, Bluetooth, wireless charging and a lithium polymer battery. A hub was also designed to communicate with the individual EDGEs through Bluetooth and send and receive data to/from the internet through Wi-Fi. Furthermore, the hub works as a charging station for the individual EDGEs. EDGE can also remotely control a wall socket through Wi-Fi. The device communicates with the user for example through the web page, phone and tablet applications and twitter. Some examples of how EDGE can be used with home appliances include sensing when the washing machine is done (vibration), when the kettle is boiling (sound) and when the sauna temperature and humidity is as desired (temperature or humidity). EDGE is an open source device which enables customers to tweak and develop it if wanted, to better match the customers individual needs and to 8

9 further develop EDGE. However, EDGE is user friendly and has a lot of applications that are already programmed and thus people with no programming skills can also use it without difficulty. Figure 4: Computer render of EDGE on its hub. 2.6 Concept design and prototyping The casing for the system needed to be created and some of the chosen characteristics of it were: small size, attractiveness, ability to be removed and repositioned, etc Concept generation After a brief discussion and agreement on the approximate size the team was looking for, the team members had a fast brainstorming session where each member would suggest a few shapes or concept ideas. Then those were shared, discussed and commented and 6 concept ideas were selected to be modelled in foam that would be created to get a more realistic feeling of how it would look and feel. From those original ideas a number of variations were also modelled. Those models were commented and iterated with small and big changes suggested by all the team members. A total of around 50 different foam models were created after this process. Figure 5: Foam models of possible shapes. 9

10 2.6.2 Evaluation Some concepts felt wrong straight away and were discarded, while others required some iterating to get the right look that the team was after. One of the concepts was starting to become the favorite, so a quick prototype of that one was made by 3d printing to get an even more realistic feel of it Selection The choice was made through voting, where each member of the team assigned 1, 2 and 3 points to their favorite designs among the models that were still in competition. The concept that had been favorited from some time before was the chosen one. Figure 7: Sketch of the chosen design Figure 6: Sketch of the chosen design 10

11 2.7 Prototyping Figure 8: CAD model exploded view. Figure 9: CAD model side view. 11

12 Figure 10: CAD model top view ELECTRONICS The creation of the working prototype started right away as the sensors were being received, tested and mapped. The first prototype, and the most reliable, was the breadboard prototype on which all of the sensors and electronic components were mounted to be tested and programmed. Once the team was satisfied with the condition of the breadboard prototype at the moment, a schematic of the setup was sketched and Circuit board was designed in the free software EAGLE. The first Printed Circuit Board (PCB) was designed to be mounted on the Arduino UNO Wi-Fi shield Ada Fruit CC3000. This PCB Figure 11: Breadboard prototype 12

13 did not work properly and because more programming had to be done the team went back to the breadboard prototype. Meanwhile, at team meetings, the functionality and necessity of the sensors were reevaluated. It was decided that the smoke and flammable gas sensor was unreliable, bulky, consumed too much power, and became too hot, so it was removed from the prototype. In addition, if the sensor was to be used as a fire detector by a user and it failed to function correctly, it would cause safety issues down the line. The opaque dome covering the motion sensor was also deemed too bulky to be fitted inside the designed enclosure. The team removed the Figure 12: PCB prototype V. 1 dome and tried the sensor with different covers to replace the dome; such as clear, light blue, dark, and cloudy plastic sheets. The cloudy plastic sheet, which has the closest resemblance to the original dome, performed the best. In the following team meetings the necessity of control and actuation was brought up. As a result the team decided to experiment with remote controlled wall socket controllers for possible candidate as the actuation of the system. A set of 3 wall socket controllers that could remotely be turned on and off with a remote controller were purchased, the remote controller was taken apart and studied, and the functionality of each button was mapped. The team figured out an extra functionality for the controller that was not initially designed into the product, that being able to turn all of the units on at the same instant. It was decided that the controller board could be reduced in size and be incorporated into the final PCB. Figure 13: PCB prototype V. 1 with mounted sensors Adding more lines of code and functionality to the system uncovered some limitation to using the Arduino UNO. Issues such as lack of space for the code and small RAM. Consequently, the team decided to switch to Teensy V.3. This also meant that the overall size could be reduced as well. At this point the code was further defined, the final lineup of the sensors to be incorporated into the product were chosen, and the electronic components were finalized. A comprehensive schematic of the final setup was sketched and a new PCB was designed. This design consisted of a double decker circuit board that housed the Teensy, Wi-Fi shield, surface mounts, and the sensor breakout boards. Lack of experience in design and making of PCB s translated into a long development time and more headache when troubleshooting. 13

14 In addition to the new PCB a lithium ion battery with wireless charger was added to the package. The battery and its charging circuitry was borrowed from a phone charger. At the moment, however, the battery is not very reliable and more testing is necessary. Figure 15: Space estimation Figure 14: PCB V.2 bare board 14

15 Figure 17: PCB V.2 wired. Figure 16: PCB V.2 Wired Figure 18: PCB V.2 Wired and stacked 15

16 2.7.2 PROGRAMMING The program can be separated to three different elements, reading the sensors and analyzing the given data, hosting the web page which serves as a user interface, and comparing the sensor values to the threshold values given at the UI and executing given tasks when threshold values are reached Reading sensors Sound and light sensor are traditional resistive sensor so the values are read with analogread. The proximity sensor pulls up the signal pin when movement is detected, so the pin is read with digitalread and if the pin is high a Boolean flag is set true. Temperature, humidity and accelerometer are digital I2C sensors. The values are read with the help of libraries provided by the manufacturers. The values of the analog sensors are not mapped due to lack of time, so the values that are shown are arbitrary Web UI The Wi-Fi chip in the device itself acts as webserver. When the device is booted, it connects with a predefined Wi-Fi access point (router) and acquires an internal IP through DHCP. On the router the MAC address of the Wi-Fi module is reserved so every time it connects it is given the same internal IP. The router has a static IP provided by Aalto IT and port forwarding is applied on the router so that when connecting to the world IP on port 80, the router forwards the client to the internal IP of the Wi-Fi module of the Edge. When the setup program of Edge is complete it continually checks for clients. When a client connects it reads the header of the request and if it is a GET request it prints the webpage in HTML to client and the client browser now can see the webpage UI provided by Edge. The domain name of edgeiot.noip.me is registered at a free DNS supplier so that the domain name points to the IP provided by Aalto which makes it easier to find the page by not being forced to type the IP but just edgeiot.noip.me in the URL of the browser. Figure 19: Web page 16

17 2.7.5 Executing Actions In the web UI one can program actions for when conditions set are met i.e. when the value of light surpasses the value provided, EDGE does the action set. These actions at the moment are: EDGE tweets a message and turn an electrical socket either on or off. These settings are made in the browser with the help of HTML forms. Since the forms are made with the GET method, the settings are seen in the URL. The text in the URL goes to the Teensy and is then parsed and saved in appropriate variables. The sensors are read every time the code loops, also the saved thresholds are checked and if the conditions set in browser are met the set action is done. Figure 20: Settings in HTML form Actuation The aim of this project was to develop a system of sensors that could be read and monitored online, as well as perform some basic actuation in the physical world in response to a set of programmed conditions. To do so, a kit of 3 RF wall socket adaptors were purchased and integrated in the system. The remote control was taken apart and analyzed to see which leg of the IC were responsible for each action. After which the remote PCB was mapped and trimmed to a smaller size to fit inside the casing. In the process of switching the board using the micro controller instead of the physical switches the team learned that the IC chip was very sensitive where even the smallest noise in the system triggered it. To succumb this, an optoisolator (Vishay 4N32) was used for each switch to isolate the microcontroller output form the remote controller IC input. Further into the integration of the remote controller, it became evident that integrating all 3 wall plugs will be impossible. As a result, only one wall plug was integrated into the system CASE The case was the most tangible part of the product and therefore, there was a deliberate intention to put time into making it look and feel good, while being functional and maintain the desired features. To do that, a dedicated sub-team modelled the part in CAD (PTC Creo Parametric 2) a three piece assembly consisting of a mounting Figure 21: Case evolution plate where the electronic components will rest on, a surrounding case and a translucent roof that will allow the light sensor, motion sensor and led to be functional. 17

18 2.8 Product and Process validation The final product was evaluated based on the previous steps taken which were designing and prototyping. The main product is the EDGE bundle and will be evaluated in this chapter in how the final designs, components and functionality of the product finally turned out. Through a validation checklist all sensors and other components were evaluated based on this test Testing and validation All the sensors had been first tested separately with their own program running in the Arduino software. In the next stage all sensors were tested together. A level shifter were made in order to combine the components that required different voltage inputs. After that all components were tested with an own made PCB. With the PCB it was possible to use surface mounted components and was good because it made it possible to fit all the sensors in the previously made EDGE bundle case which were one of the main goal to get it as close to a final product as possible. Final testing were conducted with all the components and sensors in the final PCB. A Validation Checklist were made to evaluate the functionality of all the final components and sensors on the new PCB. The table below is based from the result from testing all the sensors and components in the final PCB. Table 5: Validation checklist of all components and parts tested on the final PCB. Blue marks all sensors, the ones marked green are other components and parts Components and Parts Work / Not work Comments Temperature Works Works with the logic level shifter Humidity Works - Motion Replaced. Now works Replaced with another motion sensor Gyro Works - Accelerometer Works Works with the logic level shifter Magnetometer Works - Sound Works - Light Works - Surface mount White LED Works Replaced resistor Wireless Battery Works Works but Acts strange. The power source follow some safety protocol Vibration motor Works Some connection problem with the White LED. Problem fixed Power Source Works - Switch Works Excluded secondary switch Case Compatibility Works New PCB including battery fits in the case 18

19 2.8.2 Technical documentation Figure 22: Schematic of Second prototype Figure 23: Layout of PCB V.2 19

20 3 PRODUCTION AND MATERIAL COSTS A rough cost estimation was done for analyzing the costs for producing a series of EDGE units. For the plastic parts (main body, bottom and top) injection molding was chosen as a production method. A list of the main electrical components and their estimated costs were made. For the hub, the production cost analysis were simplified by comparing prices of Wi-Fi routers, due to the similarity in structure and function between Wi-Fi routers and the hub. The conclusion was that one Hub could be manufactured for 10 /piece. Although this analysis is not complete, it does provide information in what areas the costs would be. 3.1 Mold and part cost for the plastic parts The estimation explained in this chapter was done according to the instructions given in the book Injection Mold Design Engineering, by David Kazmer. As a series of units were to be produced, all of the molds were selected to have one cavity each. It was decided that the molds should be manufactured somewhere where the prices are low, so that the production could be started with minimal initial investment costs. According to Kazmer, for example, Brazil would be one affordable country to manufacture the molds in. The machining of the molds is assumed to be done mostly by milling. The material for the mold base is AISI P20 Steel and the material for the cavity and core set is chosen to be D2 tool steel. As finishing methods the following were chosen: SPI A-1 (diamond polish) for the surfaces with the highest surface requirements, SPI B- 3 (grit cloth) for the surfaces with mediocre surface requirements, SPI D-3 (oxide blast) for the surfaces with the lower surface requirements. The technology used was the same for all molds: Feed system: Two plate cold runner system Cooling system: Straight lines with o-rings and fittings Ejector system: Round ejector pins Structural system: No additional support structures and planar mold parting surface The material for the main body and top was chosen to be ABS and the material for the bottom was chosen to be PC. It was assumed that the parts would be manufactured with a standard hydraulic machine or older electric machine that uses semi-automatic molding with gravity drop or high speed robotic take-out. Profit for the molder was also included in the calculations. (Kazmer 2007:43-65) 20

21 Figure 25: Main body Figure 24: Bottom Figure 26: Top 21

22 3.1.1 Formulas used for estimating the mold costs C total mold = C cavities + C mold base + C customization C total mold = Total mold cost C cavities = Cost of all cavity and core sets C mold base = Cost of mold base C customization = Cost of mold customizations, e. g. finishing C cavities = C cavity n cavities f cavity discount C cavity = Cost of 1 cavity and core set n cavities = Number of cavity and core sets f cavity discount = Cavity discount depending on the number of cavity and core sets C cavity = C cavity material + C cavity machining + C cavity finishing C cavity material = Cost of cavity and core set material C cavity machining = Cost of cavity and core set machining C cavity finishing = Cost of cavity and core set finishing C cavity material = V cavity material ρ cavity material κ cavity material V cavity material = Volume of cavity and core set ρ cavity material = Density of cavity and core set material κ cavity material = Cost of material per kilogram V cavity material = L cavity W cavity H cavity L cavity, W cavity, H cavity = Rough estimation oflength, width and height of cavity and core set 22

23 L cavity = L part + max[0.1 L part, H part ] W cavity = W part + max[0.1 W part, H part ] H cavity = max[0.057, 2 H part ] L part, H part, W part = Main dimensions of the part: length, width and height C cavity machining = t cavity machining R machining rate t cavity machining = machining time R machining rate = Labor rate for machining t cavity machining = ( t cavity volume + t cavity area ) f f cavity complexity f machining machining efficiency t cavity volume = Rough estimate of the volume machining time t cavity area = Rough estimate of the cavity area machining time f machining efficiency = Factor that accounts for the fraction of time that labor and machine time are spent on non machining activities, 25 % recommended f cavity complexity = Factor for geometric complexity of part f machining = Factor depending on what machining processes are used t cavity volume = V cavity material R material volume R material volume = Volumetric mold material removal rate t cavity area = A part surface R material area A part surface = Total surface area of part R material area = Area mold material removal rate 23

24 f cavity complexity = A part surface h wall V part h wall = Part wall thickness V part = Part volume C cavity finishing = t cavity finishing R finishing rate t cavity finishing = Time to finish each portion of the cavity and core set surface area R finishing rate = Labor rate for finishing t cavity finishing = i R cavity finishing i A i part surface i R cavity finishing = Finishing rate C mold base = US830$ + M mold κ mold material M mold = Estimation of mass of mold base κ mold material = Cost of mold material per kilogram M mold = 1330 kg m 2 L mold W mold kg m 3 L mold W mold H mold L mold, H mold, W mold = Estimation of mold dimensions: length, width and height L mold = L cavity n cavities length 1.33 W mold = W cavity n cavities width 1.33 H mold = H cavity n cavities length, n cavities width = Number of cavities across the length and width dimensions 24

25 i C customization = C cavities f cavity customizing + C mold base i f mold customizing i i f cavity customizing, f mold customizing = Factors depending on the technology used in the mold (Kazmer 2007:43-59) Formulas used for estimating the part costs C part = C mold/part + C material/part + C process/part yield C part = Total cost of molded part C mold/part = Amortized cost of the mold and maintenance per part C material/part = Material cost per part C process/part = Processing cost per part yield = Fraction of molded parts that are acceptable C mold/part = C total mold n total f maintenance n total = Total production quantity of parts to be molded f maintenance = Factor associated with the maintaining the mold C material/part = V part ρ plastic material κ plastic material f feed waste 25

26 ρ plastic material = Density of plastic material κ plastic material = Price per kilogram of plastic material f feed waste = Total % of material that is used including the scrap from the feeding system C process/part = t cycle R molding machine n cavities 3600 s/h t cycle = molding cycle time R molding machine = Rough estimate of hourly machinery and labor rate s t cycle = 4 [ mm 2] (h wall[mm 2 ]) 2 f cycle efficiency f cycle efficiency = Factor depending on type of feed system and automation level R molding machine = [ F clamp 4.7 ln(f clamp )] f machine F clamp = Clamping force f machine = Factor depending on capability of machine and associated labor F clamp = [Pa] (n cavities L part W part [m 2 ] [mton] 9800[N] (Kazmer 2007:60-65) 26

27 3.1.3 Summary of mold and part costs In table 6, the costs of the mold and cost per part for each part can be seen. Table 6: Cost of molds and cost per part EDGE Mold cost( ) Part cost( /part) Main body 2210,68 0,728 Bottom 1819,06 0,532 Top 1480,40 0,584 Total 5510,14 1, Electronics costs The prices for the main components in one EDGE were taken from Mouser Electronics web shop. In table 7, the components and their price can be seen. Table 7: Cost of main electronic components Mouser Electronics Price( ) Pcs Total price ( ) Accelerometer 3,21 1 3,21 Gyroscope 1,95 1 1,95 Magnetic Sensor 0,15 1 0,15 Temperature & Humidity sensor 2,7 1 2,7 Motion & position sensor 1,71 1 1,71 Microphone 0, ,264 Photoresistor 1,79 1 1,79 Bluetooth antenna 0, ,932 Microcontroller 1,96 1 1,96 Vibration motor 0,50 1 0,50 RGB LED 0, ,161 Wireless charging coil 0,30 1 0,30 Battery 3,50 1 3,50 Wi-Fi Socket 2,00 1 2,00 Total 21,13 27

28 The rest of the bulk electronic components and the costs of PCB manufacturing and assembly were estimated to increase the price of electronics by a factor of 1.5. This resulted in an estimated total price for electrical components of approximately 31, 70 per EDGE. 3.3 Summary As earlier mentioned the hub was estimated to cost 10 to manufacture. The cost per EDGE, including molded parts and electronics, were estimated to be 1, ,70 = 33,544. In order to take into account shipment costs and further assembly costs, the final estimation of the costs per EDGE was concluded to be 35. The team did not manage to develop the Bluetooth connection between EDGE and the hub due to time constraints. The current prototype EDGE unit connects to the router via Wi-Fi module individually. The team show cased the device in 2015 Aalto Mechatronics Circus. EDGE was received warmly by the audience often attracting more people to the EDGE booth than the other booths. 28

29 4 References Kazmer, David. 2007, Injection mold design engineering, Munich : Hanser, 412 pages. 29