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Reducing cognitive complexity with simplicity

Usability Methods for Industry 4.0

André Calero Valdez Philipp Brauner, Anne Kathrin Schaar, Andreas Holzinger, Martina Ziefle

9/26/18 1

Industry 4.0 Challenges

Transition in engineering work

§ Self-optimizing, individualized, integrated processes § Regulatory and monitoring tasks

Challenges in

§ Dealing with complexity § Managing knowledge § Sharing responsibility

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Industry 4.0 Challenges

Transition in engineering work

§ Self-optimizing, individualized, integrated processes § Regulatory and monitoring tasks

Challenges in

§ Dealing with complexity § Managing knowledge § Sharing responsibility

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Forms of complexity

Perceptual complexity

§ Gestalt theory, homogeneity, simplicity, information entropy, form complexity, visual chunking, pop-out, etc.

Task-complexity

§ Multi-variate decision making, goal complexity, input complexity, process/training, time, presentation, etc.

Cognitive complexity

§ Relational knowledge (t,s,b), planning tasks, categorization, narrativity, uncertainty

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Forms of complexity

Perceptual complexity

§ Gestalt theory § homogeneity, simplicity § information entropy § form complexity § visual chunking § pop-out, etc.

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Forms of complexity

Perceptual complexity

§ Gestalt theory § homogeneity, simplicity § information entropy § form complexity § visual chunking § pop-out, etc.

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Forms of complexity

Perceptual complexity

§ Gestalt theory § homogeneity, simplicity § information entropy § form complexity § visual chunking § pop-out, etc.

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Forms of complexity

Task-complexity

§ multi-variate decision making § goal complexity § input complexity § process/training § time (duration, pressure) § presentation, etc.

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Forms of complexity

Cognitive complexity

§ relational knowledge

• transitiviy, symmetry, binary

§ planning tasks § categorization § narrativity § uncertainty § etc.

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Use-Cases

Visualization of complex data (ERP)

§ Monitoring tasks, multivariate tasks § Decision-Support => Consequences

Simulation and scientific visualization

§ Burden of knowledge § High-dimensional data

Implications for UI Design Processs Associated Costs?

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Experimental setup

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Stock Production Due in Demand 12 3 4 15 9 1 22 11 1 9 12 17 8 2 39

Experimental setup

n Controlled experiment in Supply Chain context n Independent variables

– Task complexity (within subj.) – Information Amount (within subj.) – Presentation format / Usability (between subj.)

n Explanatory variables:

– Age, Gender, Experience

n Dependent variables

– Performance (time in ms) – Correctness (correct / no correct) – Instruction: Correctness

n Order necessary in ANY for any of the lines? (Y/N)

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Results: 3-way Interaction

Poor usability especially pricy in complex environments

5000 10000 15000 20000 25000 short (4 lines) long (8 lines) Reaction time [ms] Table length simple medium difficult 5000 10000 15000 20000 25000 short (4 lines) long (8 lines) Reaction time [ms] Table length simple medium difficult

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Designing Methods

Qualitive Findings from Interviews

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Summary & Contact

Different forms of complexity

§ Visual, Cognitive, Task-based

Complexity reduction

§ Dimension reduction, pattern detection, interaction design, natural mapping

Usability methods

§ Scenario-based/Use Cases § Paper-Prototyping

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André Calero Valdez

§ calero-valdez@comm.rwth-aachen.de § 0241 – 80 239480