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@PHDTHESIS{Heuser:849648,
author = {Heuser, Patricia},
othercontributors = {Letmathe, Peter and Vossen, Thomas},
title = {{E}mployee skill development in manufacturing: consequences
of learning and forgetting on production planning and task
scheduling},
school = {Rheinisch-Westfälische Technische Hochschule Aachen},
type = {Dissertation},
address = {Aachen},
publisher = {RWTH Aachen University},
reportid = {RWTH-2022-06937},
pages = {1 Online-Ressource : Illustrationen, Diagramme},
year = {2022},
note = {Veröffentlicht auf dem Publikationsserver der RWTH Aachen
University; Dissertation, Rheinisch-Westfälische Technische
Hochschule Aachen, 2022},
abstract = {The pressure on manufacturing companies is increasing with
global competition, technical advances in production
technology, and increasingly changing individual customer
wishes. Product life cycles are decreasing, forcing
companies to invest in new product developments, which
results in production ramp-ups. Actively and efficiently
managing the ramp-up phase of production with its inherent
uncertainties may yield a competitive advantage for
companies. High demand variation, high prices paid for newly
introduced products, and a workforce that needs to get
accustomed to the new production processes characterize this
phase of low capacity utilization. Especially during the
ramp-up phase, managing employees' competence development is
of utmost importance. In addition, the digitization and the
automation of production are changing the competencies
required for production as well as the responsibilities
placed on employees. Therefore, the adjusting and the
maintaining of the worker's skill portfolios have become
crucial factors of success. This dissertation analyzes the
impact of human competence management on manufacturing
production. In this context publications and methods from
the fields of operational research and management science
are the main focus. For this purpose, four individual
research papers analyze different aspects of competence
management in production. These research articles, which
form the second part of the dissertation, are guided by a
first introductory part. This introduction connects the
articles in an overarching research model and question to
provide a larger picture. In this vein, the drivers
motivating this dissertation as well as the methods utilized
to address the research questions and the article's key
findings, together with their implications and limitations,
are described. First, an overview of the extent to which
competence management is already covered by the literature
is presented in order to guide researchers and practitioners
alike. Therefore, structured literature reviews are
conducted in Research Paper 1 and Research Paper 2. The
publications are clustered to make the state of research in
the different areas easily accessible. One stream of
literature focuses on empirical results and their
manifestation in mathematical models as well as learning and
forgetting curves. The underlying dynamics further impact
different stages of organizational planning and therefore
form the base for different optimization and planning
models. Human competencies and their target-oriented
development influence strategic as well as operational shop
floor decisions. For organizational decisions, the influence
of competencies accompanies production decisions from
creating new knowledge and product designs to planning the
production plant, timing implementing changes, and selecting
as well as training the workforce. On an operational level,
individual production environments are affected differently
by aspects of competence management. Therefore, for the
areas of assembly line balancing, cellular manufacturing,
economic order quantity, machine scheduling, and worker
assignment, the differences are elaborated together with
gaps in the existing research. Motivated by the variety of
literature on machine scheduling, which presents several
different learning effects while mostly neglecting
forgetting effects and training approaches, the results from
this field are analyzed more closely. On the one hand, a
survey article Research Paper 2 is presented that moreover
introduces a unified notation. On the other hand, a new
processing time effect incorporating learning and forgetting
into single machine scheduling is introduced in Research
Paper 3. This effect addresses a research gap identified in
the second article by including an interruption-based
forgetting effect in processing times. This effect further
accounts for mass customization developments and shared
production lines by assessing different product categories.
Hereby, the paper aims to address a second gap in research
that concerns ramp-up management for small batch production.
Solution methods addressing two relevant objective
functions, the makespan and the total completion time, allow
the inclusion of forgetting effects in scheduling problems.
A computational study benchmarks the results of a
combination of different heuristics against the standard
solution method utilized when learning effects are
considered. The results emphasize the importance of
including forgetting effects in production planning.
Different studies highlight the importance of training
measures: for example, to gain a flexible workforce, to
react to demand volatility and altering customer wishes, or
to reduce employees' boredom and to counter forgetting.
Since training, besides learning and forgetting, is a main
driver of employee development, Research Paper 4 sheds light
on the interplay of these concepts. Precisely, the effect of
budgeting the available training measures on employee's
skill development is analyzed in a production environment
with variable employee capacities, different levels of
demand volatility, as well as task and worker heterogeneity.
Results indicate that flexible training concepts,
characterized by an all-time availability of training
measures to employees, foster the skill development of
employees. In particular, the total amount of training
measures necessary to achieve a comparable level of skills
at the end of the planning horizon is higher if training
measures are budgeted. In the same manner, the amount of
knowledge forgotten increases when budgeting is employed.
These negative effects on the workforce's skills are
amplified by demand volatility and limited employee
capacity. In a nutshell, the dissertation initially provides
a holistic overview of competence management in production.
It later focuses on machine scheduling by introducing and
evaluating a forgetting effect, and it closes by analyzing
the mediating effect of training on learning and forgetting
effects summarized in employees' skill development.},
cin = {812110},
ddc = {330},
cid = {$I:(DE-82)812110_20140620$},
typ = {PUB:(DE-HGF)11},
doi = {10.18154/RWTH-2022-06937},
url = {https://publications.rwth-aachen.de/record/849648},
}
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