Human-Centred Automation to Simplify
the Path to Social and Economic
Sustainability
The Duy Nguyen and Jörg Krüger
Abstract Musculoskeletal Disorders (MSDs) pose a serious threat to sustainability
in manufacturing. In particular, this phenomenon impacts the sustainability indica-
tors of worker health and safety and the Gross Domestic Product (GDP).
Effective MSD prevention measures would therefore constitute a remarkable con-
tribution to social and economic sustainability. This chapter provides first an outline
of existing methods to prevent MSD at the workplace. Analysis of the approaches
yields that effective solutions require earmarked finances as well as qualified per-
sonnel, both of which are not affordable for many companies. In pursuit of solutions,
Human-centred Automation (HCA), a recent paradigm in manufacturing, proposes
the design of manufacturing systems using intelligent technology to support the
worker instead of replacing him/her. HCA has the unique potential of reducing the
effort needed to implement MSD prevention strategies by simplifying the path to
social and economic sustainability. This chapter demonstrates this process with the
example of the “Working Posture Controller”(WPC), which illustrates how the
HCA concept can be applied. Finally, the lessons learned from the case are outlined,
providing a vision of how future workplaces can benefit from HCA.
Keywords Musculoskeletal disorders Human-centred automation Human-
machine interaction
1 Work-Related Musculoskeletal Disorders—A
Sustainability Challenge
The health of the workforce is vital for social as well as economic sustainability.
The Guideline for Social Life Cycle Assessment of Products (Benoît et al. 2010)
describes “worker health and safety”as a major impact category among social
T.D. Nguyen (&)J. Krüger
Technische Universität Berlin, Berlin, Germany
e-mail: [email protected]
©The Author(s) 2017
R. Stark et al. (eds.), Sustainable Manufacturing, Sustainable Production,
Life Cycle Engineering and Management, DOI 10.1007/978-3-319-48514-0_6
85
sustainability indicators. In terms of economic sustainability, direct costs due to
unfavourable working conditions reduce a country’s Gross Domestic Product
(GDP) (Bevan 2015), which is considered to be one of the main economic sus-
tainability indicators defined by the United Nations—Department of Economic and
Social Affairs (2007).
Musculoskeletal Disorders (MSDs) present a serious threat to the health of the
workforce, and thus, to sustainability. The European Agency for Safety and Health
at Work (Schneider et al. 2010)defines MSDs as “health problems of the locomotor
apparatus, which includes muscles, tendons, the skeleton, cartilage, the vascular
system, ligaments and nerves.”Work-related or Occupational Musculoskeletal
Disorders (WMSDs) encompass all MSDs that are caused or worsened by work.
WMSDs as a sustainability indicator are not explicitly mentioned in the “health
and safety”impact group in Benoît et al. (2010). However, this represents more of
an oversimplification of the guideline than a negligible effect. In fact, the only
measures which are considered are those which result from suboptimal working
conditions, such as the number of injuries or accidents (Chang et al. 2016).
Accumulative effects, such as WMSDs go completely neglected although they pose
a comparable impact. The European Labour Force Survey (Camarota 2007) con-
cluded that MSDs accounted for 53 % of all work-related diseases in the EU-15,
therein representing the most frequent cause (Bevan 2015). The number of lost days
due to WMSDs is estimated at 350 million (Delleman et al. 2004) in the EU. In
terms of economic sustainability, WMSDs significantly reduce the GDP of the EU.
The total costs of WMSDs is estimated at 240€billion, which translates into up to
2 % of the EU GDP (Bevan 2015).
Due to its impact, researchers from different scientific disciplines, such as human
factors science, medicine and engineering, have developed methods to prevent
WMSDs, reducing their risk of occurrence. Significant successes have been
achieved. On average, methods implemented have turned out to cover their total
costs in less than 1 year (Goggins et al. 2008). Nevertheless, implementing effective
measures requires tedious work on the part of highly qualified ergonomists, which
makes effective WMSD prevention not realisable for every company.
Human Centred Automation (HCA) denotes a recent development in manu-
facturing technology. This engineering paradigm proposes turning away from fully
automated production lines in favour of systems where man and machine collab-
orate and combine the strengths of both participants. Instead of replacing the
worker, the machine’s task is to support him/her. The system can enhance cognitive
skills through intelligent sensors or provide additional physical capabilities through
actuators. By automatising the parts of the WMSD prevention methods which
require highly skilled personnel or tedious work, HCA helps to make these tech-
niques available to a broader mass. To sum up, the contribution of HCA to sus-
tainability lies in providing access to sustainability enhancing techniques.
This chapter concentrates on one main risk factor causing WMSDs: unfavourable
working posture, which is often referred to in literature as “awkward posture”
(Delleman et al. 2004). An exemplary technique is presented on how HCA can be
applied to solve existing WMSD prevention problems, and thus, support
86 T.D. Nguyen and J. Krüger
sustainability goals in manufacturing. Section 2provides an overview of common
state-of-the-art approaches in tackling WMSDs, outlining a fundamental problem:
the effectiveness–flexibility trade-off. The HCA, which appears to be a promising
solution to the effectiveness–flexibility trade-off, is presented in Sect. 3. Afterwards,
Sect. 4presents the Working Posture Controller (WPC). The WPC is a device which
demonstrates how the HCA paradigm is used to overcome the effectiveness–flexi-
bility trade-off. Finally, this chapter concludes with the facts learned.
2 State-of-the-Art of WMSD Prevention
Due to its high impact on human health and the economy, the area of WMSD
prevention is an extensive research field. Researchers from various disciplines such
as, human factors, medicine or engineering, have proposed their solutions. In sci-
entific literature, the measures are often referred to as “ergonomic interventions.”
This section outlines the most important developments.
In brief, the techniques presented can be grouped into three categories: technical
measures, organisational measures or individual measures (Van der Molen et al.
2005). Alternatively, Bergamasco et al. (1998) use the term “training”instead of
individual measure.
Technical measures involve modifications of the working environment and the
process. Examples include designing the workplace layout, process design, or the
introduction of special equipment to support the worker. Workplace layout design
aims at rearranging the workplace geometry in such a way that tasks can be effi-
ciently accomplished without the need for adopting awkward postures. To that
effect, ergonomic guidelines have been released to provide the workplace designer
with a tool for checking the appropriateness of the developed workplace (Das and
Grady 1983). The set of ergonomic guidelines is complex and highly dependent on
the tasks at hand and on the individual person. Often, multiple physical prototypes
have to be evaluated (Delleman et al. 2004). Digital Human Models (DHM) have
become a popular method for assisting in the design process (Lämkull et al. 2009)
by means of simulating the prototypes. Technical measures also imply the intro-
duction of equipment, such as lifting aids or human robot collaboration systems to
execute physically demanding tasks on behalf of the worker (Krüger et al. 2009;
Busch et al. 2012; Weidner et al. 2013; Schmidtler et al. 2014). Another type of
equipment is found in alert systems which monitor the process and warn the user as
soon as an ergonomically unfavourable situation arises (Vignais et al. 2013).
In addition, organisational measures (Paul et al. 1999) entail techniques which
aim at avoiding an inacceptable amount of load through customised and calculated,
balanced scheduling of the tasks. The idea is to compose the set of tasks for a
worker in a way such that multiple regions of the body are alternatingly strained.
This avoids the monotonous strain of one particular body structure leading to
long-term damage. This technique is called job rotation.
Human-Centred Automation to Simplify the Path …87
Finally, individual measures (Engels et al. 1998) supply the worker with basic
knowledge about best practices so as to enable the preservation of one’s own health.
This can include biomechanical theory, general ergonomics, or techniques e.g. for
lifting. Often, the theoretical courses are complemented with practical training.
Multiple approaches are available for tackling the WMSD dilemma.
A decision-maker has the challenge of selecting the most promising approaches to
be implemented. To that end, Goggins et al. (2008) have proposed a scale for
ranking the measures according to their effectiveness (see Fig. 1). The scale is
based on a Cost-Benefit analysis derived from the review of around 250 studies in
industrial as well as office environment. This scale comprises four classes:
•measures that completely eliminate the exposure (level 1)
•measures that reduce the level of exposure (level 2)
•methods that reduce the exposure time (level 3)
•and methods, whose success merely rely on the worker’s behaviour (level 4).
Level 1 methods are the most effective ones whereas level 4 methods should
only be considered if the other measures are infeasible.
Apart from their effectiveness, the specific amount of effort required to imple-
ment the measures has to be considered. The techniques can be grouped into two
categories: pre-process techniques and in-process techniques. Pre-process tech-
niques require the effort attached to tailoring the method to the individual task and
user groups at hand. In changing the production environment requiring flexible
production systems, these measures can produce a bottleneck. Examples are
workplace design or organizational measures. In-process measures, on the other
hand, only require one initial setup routine and then adapt to changing situations.
Examples are found in so-called cobots or alert systems. Their impact is however
limited, since their adaptation normally only covers few well-defined cases. In
conclusion, a fundamental trade-off exists between the effectiveness and the flexi-
bility of the ergonomic intervention techniques.
Though entailing tremendous effort, Goggins et al. (2008) state that the impact
of the interventions measured has been highly promising. Incidence rates have, for
example, dropped by 65 % on average and companies had to pay 68 % of the
original compensation costs after intervention. Additionally, the productivity of the
workforce and the quality of the products have improved. Most notably, these
Fig. 1 Scale of effectiveness
according to Goggins et al.
(2008)
88 T.D. Nguyen and J. Krüger
effects appear within less than 1 year after implementation. The challenge lies in
addressing how to achieve a high effect without losing out on flexibility.
3 The Potential of Human-Centred Automation
(HCA) for Sustainability
With the introduction of computers, manufacturing has been veritably revolu-
tionised. Tasks which had been time-consuming and tedious can now be efficiently
performed with relative ease. At the same time, tasks which originally required
human experts have been simplified in such a way that lower skilled operators can
use them.
In recent years, techniques of Human-centred Automation (HCA) have become a
matter of research. The original term comes from the domain of aviation and was
introduced by Bilings (1997). HCA describes a novel approach in system design. It
proposes building an environment, “in which humans and machines collaborate
cooperatively in order to reach stated objectives.”This paradigm has been applied
in various systems, such as driver assistance systems, aircraft flight management
systems and air traffic systems.
Furthermore, HCA has increasingly become a matter of research in manufac-
turing. In this domain, HCA represents a new paradigm of turning away from full
automatisation as a long-term goal, and instead moves in the direction of achieving
more flexible manufacturing structures. Systems of HCA strive to support the
worker rather than to replace him/her with technology. The human remains the core
of the process and the technology is used to enhance cognitive skills by sensors and
physical skills by actuators. The result is a production system wherein worker and
machine are tightly bound together, combining one other’s strengths and com-
pensating for each other’s weakness.
To be sure, both human and automation systems have their advantages and
shortcomings. Humans are highly flexible insofar as being able to learn new tasks in
a short time. Yet, the human is vulnerable. Automation technology with its actu-
ators proves however to be quite powerful and can efficiently accomplish repetitive
tasks. On the other hand, flexibility is lost in that process, since programming the
machines likewise takes time and is work intensive, making it only suitable in high
lot size production scenarios.
Recent developments in the field of intelligent systems have made it possible to
develop systems which support the human in a more sophisticated manner. The
trouble with the solutions mentioned in Sect. 2is that they require human expertise.
Considering the lack of experts to implement the solutions, the only way to escape
this dilemma is to teach machines to take over some of the tedious as well as
sophisticated manual tasks. In this way, HCA can help to implement measures
designed to reduce health risks at the workplace with an acceptable level of effort.
Human-Centred Automation to Simplify the Path …89
4 The Working Posture Controller (WPC)
WMSDs present a grave problem for the manufacturing community. Especially
considering the ageing worker population in many countries, these disorders are
poised to become a significant sustainability challenge. Remarkable effort has been
put into solving the WMSD issue. Yet, a fundamental trade-off in the solutions
proposed stands at the crossroads: either the measures are effective but inflexible, or
they are easily adaptable but less effective. Nevertheless, some experts have con-
cluded that HCA techniques are starting to make an impact on manufacturing by
combining the best of both worlds. A particular motivation for HCA has been the
need for flexibility without the need to relinquish the advantages bestowed by
automation technology.
All these facts taken together indicate that the solution to the problem seems to
lie in applying HCA techniques to confront the WMSD challenge. The questions to
be posed are: What exactly do the resulting systems look like? How can such
systems be technically realised? This section attempts to provide answers by pre-
senting an exemplary device: the Working Posture Controller (WPC) (Krüger and
Nguyen 2015; Nguyen et al. 2016).
The WPC is a system that continuously monitors the worker’s posture in the
process and adjusts the workplace layout when the combination of task and
workplace does not allow for a natural working posture. Through automatising the
work and knowledge-intensive parts in the highly effective measures, flexibility is
gained.
4.1 Concept of the WPC
The main conceptual idea of the WPC is to combine automatised ergonomic
assessments with automatised workplace design into one system. This system
enables the user to avoid adopting awkward posture for prolonged periods. In the
workflow, man and machine are embedded into a control loop. Figure 2depicts one
full sequence. A posture assessment module monitors the worker’s posture,
assigning a numerical score which represents the current postural load of the task. If
the score exceeds a particular value, the system initiates the posture optimisation
module. This component first interprets the worker’s posture to interpret which task
he/she intends to accomplish. Afterwards, it computes a workplace layout adjust-
ment which enables accomplishing the same task with a more ergonomic posture.
Having found this adjustment, the system then gives feedback to the user, providing
a visual of the proposed workplace geometry and posture. Once the worker agrees,
the adjustment is executed. Upon adjustment, the cycle then starts anew. The
coming subsections describe the two components in further detail.
90 T.D. Nguyen and J. Krüger
4.2 Posture Assessment
The posture assessment module is based on the “Ergonomic Assessment Worksheet
(EAWS)”(Schaub et al. 2013), a manual tool to help ergonomic practitioners
assessing working tasks. The whole concept behind it is that the practitioner
observes the task and assigns load points for the duration of the particular working
postures adopted. The EAWS defines a set of postures which have to be recognised
from observation. The accumulated score of the single posture durations yields the
overall postural risk score.
Automatising this posture assessment process requires the system to automati-
cally recognise the right posture from the defined one. The WPC uses a consumer
depth camera to acquire the input data. Afterwards, a markerless motion capture
algorithm (Nguyen et al. 2014) is developed to determine the coordinates of each
limb. Having obtained the coordinates, classifiers are trained on training datasets to
recognise the posture. Upon recognition, load points can be assigned and the
current risk score can be accumulated accordingly. If this ergonomic score exceeds
a given threshold, an adjustment is then initiated.
4.3 Posture Optimisation
Having detected the ergonomically critical situation, the posture optimisation
algorithm attempts to compute an alternative workplace adjustment where the
worker is able to accomplish the same task in a healthier posture.
The algorithm first interprets the original task intended from the recognised
posture. Relevant parameters to be detected lie in the orientation of the upper arm
and the location of the hands relative to the workpiece. Afterwards, the algorithm
searches for an adjustment of the workplace geometry, which enables accom-
plishing the task in an ergonomically more favourable posture. The biggest chal-
lenge lies in mathematically modelling the human behaviour at hand. The posture
Fig. 2 Concept of the WPC. An actuator, in this case a robot, holds the workpiece to be
processed. Additionally, a sensor system monitors the worker’s posture. In case the posture
becomes physically straining, the WPC proposes the change to the workpiece pose, making it
possible for the user to adopt a more natural posture
Human-Centred Automation to Simplify the Path …91
adopted once a potential adjustment has been taken, then has to be predicted. The
behaviour is modelled by transforming the task into non-linear mathematical
optimisation problem which can be solved with standard optimisation algorithms.
Different types of actuators yield different optimisation problems. An exemplary
visualisation of original and predicted posture after adjustment is depicted in Fig. 3.
5 Discussion and Outlook
WMSDs have a high negative impact on social as well as economic sustainability.
The WPC shows that HCA can be successfully applied to improve WMSD pre-
vention methods. This novel way of preventing awkward posture combines sensors,
intelligent algorithms and actuators to enable the machine to perform tasks which
would normally require human expertise in less time. Through the time-intensive
and tedious process of setting up the parts of the workplace design to fit the
automation technology, the whole production system gains the flexibility required.
The system is designed to be usable with cost-efficient as well as advanced hard-
ware in order to address a broad group of users.
Fig. 3 The red manikin
denotes the current posture
whereas the green manikin
denotes the optimised
working posture after
adjustment
92 T.D. Nguyen and J. Krüger
Implementing HCA concepts into further manufacturing requires a discussion of
the fundamental problems of man-machine interaction. First of all, engineers have
to define the appropriate level of automation (LoA) for the given system. The term
LoA is defined by Frohm (2008)as“allocation of physical and cognitive tasks
between humans and technology, described as a continuum ranging from totally
manual to total automation.”The problem is summed up by the question: what is
supposed to be done by the human and what is supposed to be done by technology?
The answer to this question will influence what such systems look like, and in what
manner they assist the worker. Second, after defining how to allocate the task,
designers have to define how human and technology are supposed to communicate.
This aspect is critical for the acceptance of HCA. Common mistakes in the design
of communication between human and machine are described in such works as
Endsley’s(1995).
To conclude, HCA stands as a promising means of supporting social and eco-
nomic sustainability goals. However, designing these systems is challenging, since
it is not known exactly what form they ultimately take. The WPC, among other
projects, has shown one example of how such a system can be designed.
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