Today’s shop floor, the area of a factory where operatives assemble products, is a complex and demanding work environment. The employed and produced technology becomes ever more complex, and employees are responsible for an increasing amount of tasks. As a consequence, the employee is under constant pressure to solve problems occurring on the shop floor as fast as possible, and simultaneously to improve his work-related knowledge, skills, and capabilities. This paper gives an account how adaptive technology can support the employee on the shop floor in these respects. It describes the organizational requirements to take into consideration and describes a set of rules that support the employee in problem solving and knowledge acquisition.

1. Rules for Adaptive Learning and
Assistance on the Shop Floor
Carsten Ullrich
Associate Head
Educational Technology Lab (EdTec)
at the
German Research Center for Artificial
Intelligence (DFKI GmbH)

2. The Workplace is
Transforming
• Challenges for Europe's manufacturing industry:
– Accelerating innovation
– Shorter product cycles
– Ever increasing number of
product variants
– Smaller batch sizes
(batch size 1)
– … while keeping/increasing level
of competitiveness
– … with fewer and fewer employees
Carsten Ullrich, Rules for Adaptive Learning and Assistance on the Shop Floor

3. Human Operators at
Tomorrow’s Workplace
• Despite the increasing automation, human operators have
place on shop floor  with changed roles
• Technological innovation cannot be considered in isolation, but
requires an integrated approach drawing from technical,
organizational and human aspects.
• Industry 4.0 and other new technologies increase complexity of
– usage and maintenance of production lines
– control of the production process
• Employee under constant pressure
– to solve problems occurring on the
shop floor as fast as possible,
– to improve work-related knowledge,
skills, and
capabilities
Carsten Ullrich, Rules for Adaptive Learning and Assistance on the Shop Floor
(Hirsch-Kreinsen, 2014)

4. Assistance- and Knowledge-Services
for Smart Production
• Information providing and training processes have to become
– more flexible
– integrated in the workplace
– individualized
• Opportunity to build tools that
– adapt themselves intelligently to the knowledge level and tasks of
the human operators
– integrate and connect the knowledge sources available in the
company
– generate useful recommendations of actions
Carsten Ullrich, Rules for Adaptive Learning and Assistance on the Shop Floor

5. Partly automated assembly
line
Support for maintenance
5-axis drill
Support for machine usage
Pilot Scenarios
Partner
Pilot Area
Pilot Scenario
Production line
Support for failure detection
Carsten Ullrich, Rules for Adaptive Learning and Assistance on the Shop Floor

6. 3 manual assembly
stations
Main host computer
Monitoring and analysis
SPS
Controlling the machines
Coarse control and
monitoring granularity
 System detects status and
faults
 Classification on level of
stations, not components
Activities
 Preventive maintenance
 Resolving disabled states
and faults
 Manual assembly
Goal
 Increasing the competence
level of target audience
 Increase worker’s
understanding of process,
product, manufacturing
Automated processes
Machine user
Machine operator
(plus)
Machine operator
Competence
Pilot Study: Festo
Carsten Ullrich, Rules for Adaptive Learning and Assistance on the Shop Floor

7. Artificial Intelligence in Education
• Intelligent Tutoring Systems and
Adaptive Learning Environments
provide adaptive and
contextualized support of learners
• Significant body of research on
adaptive support in university and
highly structured domains such
as mathematics, physics and
computer science
• Service-oriented architectures for
learning
Carsten Ullrich, Rules for Adaptive Learning and Assistance on the Shop Floor
Domain
Model
Learner
Model
Pedagogical
Model

8. Adaptivity in Smart
Manufacturing
• Main activity: Fulfill Key Performance Indicators (KPI)
 Assistance: Depending on the context
a) Reacting to the current situation on the shop floor, e.g.,
Loctite is empty
• Secondary activity: Time for Learning
 Learning: Depending on the employee
b) Reacting to recently occurring events (e.g., a large number
of correctly or incorrectly performed measures)
c) Long-term development goals (e.g., working towards a
new job position)
Carsten Ullrich, Rules for Adaptive Learning and Assistance on the Shop Floor

9. Carsten Ullrich, Rules for Adaptive Learning and Assistance on the Shop Floor

10. Carsten Ullrich, Rules for Adaptive Learning and Assistance on the Shop Floor

11. Carsten Ullrich, Rules for Adaptive Learning and Assistance on the Shop Floor

12. Carsten Ullrich, Rules for Adaptive Learning and Assistance on the Shop Floor

13. Carsten Ullrich, Rules for Adaptive Learning and Assistance on the Shop Floor

14. If employee is in state “main work activity” and asks for assistance, then
select work procedures relevant for current station und machine state:
1. WU = workplace unit to which employee is assigned to.
Determined through request to user-model-service.
2. S = sort(stations ∪ installation) of AG. Determined by querying
domain model: There, each workplace unit is assigned to work with
specific installations. An installation consists of stations. Sort the
stations according to priority of each station.
3. MS = machine state of S, sorted according to priority of machine
state. Determined through request to machine-information-service.
4. P = Procedures for MS. Determined through query of domain
model: Procedures are applicable to machine states.
5. P_a = those procedures of M the employee is authorized to
perform (with or without assistance). Determined through request
to user model.
Result: P_a
Select Measures, Main Activity
Examples
1. WU = (Production
of standard
cylinders)
2. I =
(DNC_DNCB_DSB
C, …) . Stations =
(S10, S20, …).
Pri(DNC)=8
3. MS = (LociteEmpty,
GreaseFew, …)
4. P = (ChangeLoctite,
ChangeGrease, …)
5. P_a =
(ChangeLoctite)
Carsten Ullrich, Rules for Adaptive Learning and Assistance on the Shop Floor

15. If the employee is in state secondary activity (“time for learning”) and asks for
procedures, then select procedures relevant to development goals (content C_A,
and/or position PO, and/or production items PI_A).
1. PO = agreed future position of employee. Determined by query to user model.
2. P = relevant work procedures for PO. Determined through query to domain
model: Each position has tasks, and work procedures perform tasks.
3. P_U = P without mastered procedures. Determined through query to user model
(which keeps track of mastered procedures).
Result = P_U.
Select Measures, Secondary Activity
Carsten Ullrich, Rules for Adaptive Learning and Assistance on the Shop Floor

16. If the employee is in state “main work activity” and asks for information, then select
content relevant for the stations assigned to and their machine states:
1. WU = workplace unit to which employee is assigned to; P = position of
employee. Determined through request to user-model-service.
2. S, MS = Machine states and stations/installations relevant for WU (see
previous rule)
3. I = Content about S∪MS for target-group = P or without target-group.
Determined by querying domain model, which contains metadata that relates
content to domain model entities and specifies its target-groups, if any.
Result = Content I.
For instance: operation manuals, circuit diagrams, and other content that provides
information about the current situation enabling the employee to overcome
occurring problems.
Select Content, Main Activity
Carsten Ullrich, Rules for Adaptive Learning and Assistance on the Shop Floor

17. If employee is in state secondary activity (“time for learning”) and asks for content, then select
content relevant to current work history (machines and procedures worked with). Development
goals: content C_A, and/or position PO, and/or production items PI_A.
1. PI = production items with which employee has worked with in the last four weeks, P_S the
procedures that she performed successfully and P_N those not performed successfully.
This information is stored in the learner-record-service.
2. C_P_N = content about P_N and production items used by P_N, with already seen content
sorted to the back (this information is stored in the learner-record-service).
3. C_P_S = content about P_S or about production items used by P_S or about PI.
4. C_P = Content that covers one/several of the following: position PO, tasks of PO, or
production entities PI_A.
5. C_PI_PO = Content that describes production entities relevant for PO.
6. C_P_PO = Content that describes production entities used for performing procedures
relevant for PO.
7. C_T = C_P_S ∪ C_P ∪ C_PI_PO ∪ C_P_PO, with already seen content sorted to the
back.
Result: Content C_P_N + C_A + C_T, with duplicates removed.
Select Content, Secondary Activity
Carsten Ullrich, Rules for Adaptive Learning and Assistance on the Shop Floor

18. Example
• John Doe:
– assembly worker, workplace group “assembly of standard cylinders”
– Cleared for “refill adhesive”.
– Development goals: learn about produced product (the standard cylinder ABC); prepare for
performing the maintenance task “replace grease barrel”.
• Fiona Smith
– machine operator, workplace group “assembly of standard cylinders”
– Cleared for all maintenance procedures.
– Development goals: Learn about Industry 4.0, standard cylinder ABC; prepare for a customer
meeting
• During their shift, adhesive & grease drop to low levels. Support:
– Procedures for John: “refill adhesive”, followed by procedure for less important tasks, such as
cleaning the work environment.
– Procedures for Fiona: “refill adhesive” and “replace grease barrel”, followed by less important
procedures.
– Content for John: security information and adhesive specification sheet
– Content for Fiona: layout of stations and technical documentation.
• Time for learning.
– Procedure for John: “replace grease barrel”
– Procedures for Fiona: maintenance procedures of the installations of the customer.
– Content for John: general technical information about the standard cylinder, a video showing how it is
used in other machines, and general information about site
– Content for Fiona: course on Industry 4.0 and specific technical information about the cylinder
Carsten Ullrich, Rules for Adaptive Learning and Assistance on the Shop Floor

19. Conclusion
• Support of problem solving and learning on the shop
floor by adaptive services
• First steps into researching adaptivity on the shop
floor on formal level
• Evaluation: System Usability Scale (Brooke, 1996)
and Think Aloud Protocol
– 6 employees of each industry partner received a number
of tasks to solve using the system
– SUS: average score of 86.9
– Think-aloud protocols did not show any problematic points
– Only first steps, further evaluations underway
Carsten Ullrich, Rules for Adaptive Learning and Assistance on the Shop Floor

20. Thank you
Carsten Ullrich
carsten.ullrich@dfki.de