Master's Thesis: User-driven Concept Development of Portable Silage Analyzer by David Qvist

USER-DRIVEN CONCEPT DEVELOPMENT OF PORTABLE SILAGE ANALYZER Master’s Thesis Individual project in collaboration with Foss 5 months

USER-DRIVEN CONCEPT DEVELOPMENT: PORTABLE SILAGE ANALYZER Master’s Thesis at DTU: 5 months in collaboration with Foss Analytical A/S

IDENTIFIED PROBLEM

Dairy cows need optimized feed to provide maximum output of milk, and are therefore fed according to meticulously designed feed ration plans. Silage, the dairy farmers own produce, which makes up 80+ percent of feed rations, needs to be analyzed to determine its nutritional values before it can be rationed. Unfortunately, these values change over time, and therefore the current setup, where silage samples are analyzed off-site, causes a delay which results in sub-optimal feed rationing.

DESIGN CHALLENGE

Based on the identified problem, carry out a transparent user-driven multi-stakeholder design process to develop a well-documented concept based on identified user needs and derived target specifications.

DESIGN PROCESS

Fig.1: Current setup, key stakeholders and value proposition

UNDERSTAND: A DAIRY FAMER Observing and interacting with a dairy farmer as he carried out his daily work routines provided the following key insights: • The dairy farmer’s main goal is to improve yield and quality of milk production. • The farmer does not have the resources, or time, to translate nutritional values of silage into optimal feed ration plans.

Fig.2: From top to bottom: The process of creating silage and using it to feed the dairy cows

UNDERSTAND: A FARM CONSULTANT A farm consultant was observed for one day as he carried out his job and processed the data that goes into creating feed ration plans. • The farm consultant possesses the tools and experience necessary for creating optimal feed ration plans for the dairy farmer. • The farm consultant relies on off-site analyses of the silage in order to finalize the feed ration plans. • Results from analyzing one sample are generally used to optimize the rationing of a silage clamp in its entirety – despite of its varying and changing nutritional values.

Fig.3: From silage sample to feed ration plan

UNDERSTAND: NIR TECHNOLOGY To be able to design for the technology that is proposed for use in the solution, three meetings served as an introduction to how near-infrared (NIR) spectroscopy works. The inherent challenges, in relation to applying NIR analyses on fresh, untreated silage, were also explained. • A good NIR solution relies on the quality of three key parameters: The sample presentation, the prediction model and the spectrometer. • FOSS possesses calibrations of very high quality relative to its competitors. • Different types of spectrometers have different requirements for sample presentation, e.g. a DDA-type spectrometer allows for the sample to be moved

while measuring, whereas a monochromator-type spectrometer does not. • The NIR solution needs to accommodate the nature of the sample: » The heterogeneous composition of fresh silage makes it difficult to analyze. » The more heterogeneous and impenetrable the sample is, the more data (area or sample points) is needed. • Only a small margin of error is permissible for the results to be of any use in optimizing the feed ration plans.

Fig.4: The principle of reflectance measurements

UNDERSTAND: GRASS- AND CORN SILAGE To develop a solution that can handle sample presentation of both grass- and corn silage, it is necessary to understand the characteristics of the two – and why it is difficult to analyze fresh silage in general. Several external factors contribute to the heterogeneous nature of silage. These include weather, soil quality, crop type and crop management. But also, the vertical variation – from the layering process – and the horizontal variation, caused by natural processes over time, contribute, along with contaminants such as dirt and weeds.

ferent species and that, once it is cut, the grass is left to dry in the fields before it is made into silage. The resulting grass silage is a relatively homogenous substance consisting of similarly sized blades and straws of grass. Corn silage Of the two types of silage, corn silage is the more heterogeneous. When creating corn silage, the entire plant is cut up, resulting in a mixture of very different constituents. In addition, the constituents vary greatly in size and similar constituents may also have different nutritional values.

Grass silage Contributing factors that are specific to grass silage being heterogeneous are that the sown grass is a mixture of dif-

Fig.5: Grass- and corn silage

DEFINE: SYSTEM PARAMETERS AND SOLUTION SPACE The diagram on the right represents the scope and the interdependencies of system parameters. The following is a list of conclusions to questions asked (section not included here) prior to the analysis: • Who is the user? » The most viable solution is to have the farm consultant be the user of the solution. • Is sample presentation done entirely by the device once the silage has been introduced, or is it up to the user to ensure correct presentation? » Sample presentation occurs on the device level to further mitigate user errors.

Fig.6: Delimited solution space depicting all interpendent parameters

DEFINE: USER PERSONA

Having established that the most qualified user is the farm consultant, his goals are captured in the form of a Persona. Input from FOSS employees was used iteratively to create a persona that can be considered an archetype.

Fig.7: Archetypical farm consultant

DEFINE: ENVISIONED USER JOURNEY To meaningfully discuss implications of future concepts from a user experience perspective, it is desirable to have a baseline. The envisioned user journey depicts is based on decisions and definitions regarding the user and the context of use. It allows for a more effective identification, and better understanding, of user needs that relate to specific parts of the journey. The journey should not in any way be considered an exhaustive list of touch points, though. It has a clear focus based on the thesis scope. The elements in red are either directly related to sample presentation (10 and 13) or depend on the sample presentation solution to a degree that they must be included when both ideating and evaluating concepts e.g. dimensions and weight (2, 4 and 5) and cleaning (19 and 20). Key elements from outside the scope are included for the sake of communicative and contextual completeness.

Fig.8: Envisioned user journey showing all relevant touch points the farm consultant will encounter

DEFINE: USER NEEDS... Identified user needs (Figure 9) will guide the following derivation of target specifications - thereby lowering the inherent risk of new product development. Of importance is that the user needs are identified and expressed independently from any and all of the specifications that relate to particular concepts chosen for further development later in the process. As was the case with the Persona, this process draws on experience from (the same) FOSS employees. This will also help better align the relative importance and lower the risk of translating the same user data into different needs. It is important to emphasize that the needs listed here are identified on the same premises as the envisioned user journey. As such, they are either directly related to sample presentation, or concern the dependent parameters portability, (parts of) usage, functionality, expected lifespan, cleaning and safety.

No. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Need Statement The device is portable Can fit in the trunk of a car. Can be carried some distance. Functions without being plugged to electric power. Can function one whole workday without the need to recharge. The device is a pleasure to use Is easy to physically set up. Does not easily fall over. Functions normally on uneven surfaces. Is easy to use. Is quick to use. Can be used in less than ideal lighting conditions (direct sunlight or in the dark) Is easy to clean. The device functions well Delivers reliable results. Functions normally regardless of weather season. The device lasts a long time (lifespan) Functions normally after small drops and bumps. The device is safe to use Does not cut or squeeze the users’ hands or fingers.

Fig.9: Qualitative user needs

Rel. Imp. 5 5 5 3 4 4 5 5 3 3 5 5 5 5 5

...AND TARGET SPECIFICATIONS Specifications are intended to remove the ambiguity of the user needs. Target specifications represent the aspirations of the following design efforts and are agnostic to any constraints that price, technology, competing offers – and the choice of concept – will impose on the project.

No. Need(s) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Metric Rel. Imp. Portablility (ergonomics and storage) 1, 2 Height of device, when not in use. (estimate) 3 1, 2 Width of device, when not in use. (estimate) 3 1, 2 Depth of device, when not in use. (estimate) 5 2, 3, 4 Total weight of device. 5 Usage 5, 6 Continuous force required to push over on level surface. 4 (Force exerted at highest point) 7 Maximum angle of tilt. (estimate) 4 8, 9, 10 Time it takes to complete sample introduction. 4 Functionality 12 Can handle both corn and grass silage 5 12 Amount of silage to be presented to the spectrometer. 5 (Note: This is an approximation) 8, 12 Analysis procedure requires no user interaction (Pres5 entation solution can reliably present silage to the spectrometer) 12 Pinholes must not exist. 5 12 The sample must be still while measuring. 5 12 No stray light from outside or from internal reflections. 5 12 Does not break up the sample. 4 12 Does not heat the sample. 5 9 Time to take one measurement. 5 9 Silage manipulation time (time between each measure3 ment). 9, 11 Time to clean completely. 5 13 Working temperature range. 5 Ruggedness/robustness 14 Robust mechanisms/construction.(placeholder for more 5 specific requirements e.g. drop height) Safety 16 Does not cut or squeeze the users’ hands or fingers. 5

Units

Ideal

Marg.

cm cm cm kg

40 40 20 5

50 50 30 6

Degrees Minutes

10 2

5 3

≈ 400

5 0-40

Binary cm2 Binary Binary Binary Binary Subjective Binary Seconds Subjective minutes °C N/A

Binary

Fig.10: Quantitative target specifications – including relative importance for each – that the success of a proposed solution will depend upon

IDEATE: MORPHOLOGICAL IDEATION A morphological approach is used to define and investigate the solution space based on a set of technological constraints (section not included here).

Fig.11: Morphological ideation

IDEATE: SYSTEMATIC CONCEPT SELECTION 14 principles remain after an initial reduction process – some with variations of the spectrometer (technology used to analyze the silage) position. The reduction process also reduces the number of target specifications needed to evaluate the remaining ideas. The ideas are then scored on a relative scale from negative two to two based on the set of remaining specifications: 1. The concept has dimensions that allow for carrying (specifications 1-3). 2. The concept is physically stable when it is set up (specification 5). 3. The presentation mechanism is reliable/requires no intervention from the user during analysis (specification 10). 4. The concept is easy to clean. Considerations include glass sur-

face area and hard-to-clean areas (specification 18). 5. The concept is robust in its mechanisms and construction. Considers number of moving parts, complexity and fragility of construction and glass area (specification 20).

1 2

Total

Weight

30%

40%

10%

20%

100%

Fig.12: Process of calculating the weight of specifications

After each principle has been scored relative to one another, the relative importance of each specification is taken into account by calculating the weight of each. Each pair of specifications is compared in a matrix, deciding which is more important, e.g. comparing criterion number one – dimensions that allow for carrying – to number two – physical stability – shows that portability is more important than stability.

IDEATE: CONCEPT PROPOSAL Calculating the weighted score reveals that the best suited concept is one that mixes the silage by means of a rotating drum fitted with internal blades perpendicular to the direction of motion. The spectrometer can be placed either below or behind the drum. The user scenario of this mixer is initially imagined as the user removing the drum from the device itself, then adding the silage, closing the drum off with a lid and then placing the drum back in the device after which the analysis procedure is begun. Concerns and variables This concept did not achieve a maximum score on reliability due to mainly two immediate concerns. One concern is the concepts' ability to mix the silage from front to back within the drum. The other concern is that pieces of silage will get stuck on the sample glass. These concerns will therefore be included in the criteria for testing and evaluating the concept. The parameters that can be varied and tested to optimize the basic principle are labelled in Figure 11 and include: 1. Drum-related variables: Dimensions and tilt. 2. Blade-related variables: Shape, dimensions, placement and number of blades. 3. Motion-related variables: Speed, number of revolutions and acceleration of drum. Fig.13: Concept proposal and variables to be investigated

BUILD: QUALIFICATION OF EXPERIMENTS To qualify the experiements, and to retrieve information that can inform decisions on what and how to test, an extensive literature search is undertaken. The following list are the key takeaways from this study: • Drum dimensions - Depth to diameter ratio: The depth to diameter ratio will be approximately 1:2. • Drum dimensions - Volume: The volume will be modelled to have the silage fill the drum at approximately 50% • Blades - Number: The tests will be performed using zero, one, two and three blades. • Blades - Pitch: To investigate the effect of pitch, an initial 30°-pitch will be included as a variable – with both cw and ccw motion. If it results in a better mixing performance, a 45°-pitch will also be tested. Variable definitions To build the prototupe it’s essential to define the values and constraints for

both fixed variables and the variables whose effect on mixing performance will be investigated. The following is a list of fixed variables: • Density of silage: Grass silage will be used due to its entangled nature. The drum will therfore be modelled according to its density (150 g/l). • Weight of silage: Technological constraints mean the drum needs to be able to hold 300 grams of grass silage. • Blade shape: The blade shape is fixed as a rectangular prism spanning the depth of the drum (from front to back). • Drum revolutions: The drum will need to manipulate the silage 128 times to reach the required area (technological constraint)

Fig.14: Drum dimensions

These are the variables that will be tested: • Number of blades: 0, 1, 2 and 3 (evenly spaced). • Pitch of blades: 0° and 30° (both clockwise and counterclockwise motion for 30°). • Tilt of drum: 0°, 15° and 30°.

Fig.16: Powder mixing schemes [Illustrations replicated from: "Monitoring and control of a continuous tumble mixer" (Velázquez et al., 2018)] Fig.15: Vertical cylindrical mixer and horizontal agitated paddle mixer

BUILD: MIXING PERFORMANCE The underlying assumption that qualifies mixing as a way of presenting new silage to the spectrometer is that good mixing performance results in new silage being presented to the spectrometer. Implicit in this assumption is that good mixing performance will essentially be assessed on how quickly the silage is mixed. This section describes how a practical mixing criterion is developed. Colored silage It is decided to come up with a way to visually evaluate how well the silage mixes. However, to evaluate how well substances mix, they need to be distinguishable from one another – and start out as separated, naturally. Therefore, the 300 grams of grass silage will be divided into two batches. One batch will be of untreated fresh silage and the other batch will need to have a color in order to visually tell when the two batches have mixed completely. Several attempt were made to find the solution with the least amount of influence on the grass silage. The best solution turned out to be a 1:1-mix of spray-painted silage and untreated fresh silage.

Presentation performance Good mixing performance is not necessarily the same as good presentation performance. The following criteria are defined to evaluate the latter: 1. After each revolution, the majority of the silage must land at the bottom of the drum and rest on its walls. 2. No silage can be stuck to the windows. 3. Silage must not be significantly broken up.

Fig.17: Spray painted grass silage

Fig.18: Assessment of whether it is possible to determine when colored and untreated grass silage have been mixed 19

BUILD: DESIGN OF EXPERIMENTS To investigate the effect of the test variables, three sets of tests will be performed: • The first round of tests concerns mixing performance and investigates the effect on number and pitch of blades in combination with various degrees of backwards tilt of the drum. • The second round of tests is based on the results of the first round and seeks to refine the best configuration of blades and drum tilt. The direction of motion is also tested. • Finally, based on the overall test strategy, the third set of tests has the purpose of investigating whether the two best performing configurations for mixing grass silage can be successfully transferred to corn silage.

BUILD: THE PROTOTYPE The prototype is depicted in Figure 19. Its features include: • 3D-printed detachable drum with inner depth = 110 mm, inner diameter = 220 mm and volume ≈ four liters. • Mounting holes for blade attachment for every 30°. • 3D-printed drum coupling designed to fit onto motor coupling. • Moons stepper motor (type 23HS2441-04) with step angle of 1.8°. • See through back- and front plate for easy observation of mixing progress. • Recessed acrylic windows inside the drum. • Recessed area between drum and rig to allow for inspection of bottom windows. • Adjustable feet for testing tilt of the drum. • Attached breadboard (for button control) and Arduino Uno with Rohm motor driver (id: BD63524AEFV) Two Arduino sketches are programmed to allow for testing both constant speed and acceleration of the drum.

Fig.19: Prototype details

TEST: CONCERNS AND UNCERTAINTIES • Corn silage appears to break up slightly, placing some lighter/larger constituents at the top of the mixed batch. • Parts of the grass silage would briefly get stuck together, forming discrete batches that did not mix well with the rest of the silage. It can be assumed that the affected tests required additional revolutions of the drum to mix the silage completely. • The results indicate that the effect of using 25% painted silage will result in a slight increase in required revolutions when only fresh untreated silage is used due to increased moisture level. • All results were based on subjective assessments. Carrying out all experiments in one setting increases the likelihood of there being an internal consistency in the assessments, but nevertheless it has to be regarded as a contributing factor in adding some uncertainty to the results.

TEST: CONCLUSIONS The overall assessment of the concept is that it has shown promising results as a viable option for solving the problem of sample presentation of both grass- and corn silage. Assessing the effect of blade configuration, drum motion and degree of backwards tilt of the drum, on mixing performance, the tests have resulted in the following findings: • Of all the tested combinations, the best performing configuration uses two non-pitched blades placed at positions 0° and 180° with a backwards tilt of the drum of 15°. • The drum should be accelerated at a rate of ≈ 133 rpm/s² to a speed of ≈ 33 rpm for grass silage and to a speed of 50 rpm for corn silage. • Finally, concerning observations were made in that residue collected on the windows and that there was a tendency of the corn silage to break up.

Fig.20: Observed issues when tilting the drum at an angle of 30°

Fig.21: Observed issue when the blades have a pitch of 30°