Creative Education
2012. Vol.3, Supplement, 25-28
Published Online December 2012 in SciRes ( DOI:10.4236/ce.2012.37B006
Copyright © 2012 SciRes.
An Exploratory Study of Batch Splitting through Combined
Control of Release and Dispatching
Nuno O. Fernandes1, S. Carmo-Silva2
1School of Technology, Polytechnic Institute of Castelo Branco, Castelo Branco,
Av. do Empresá rio 6000-767, Port ugal
2Dept. of Production and Syst ems, University of Minho, Braga, Campus de Gualtar 4710-057, Portugal
Received 2012
Workload Control (WLC) has been developed as a production planning and control approach for
make-to-order manufacturing. Previous studies on WLC often assume a simplified shop where released
batches are treated as independent jobs, which proceed through the different stages of processing without
being split. Batch splitting allows released batches to be split into a number of smaller sub-batches so that
its operations at work centres can be overlapped and its progress accelerated. This paper investigates how
WLC performs under batch splitting. Evaluating the performance of WLC in this context is an important
step towards the alignment between WLC theory and practice. Thus, assuming a production situation with
unbalanced utilizations of manufacturing resources, the effectiveness of different dispatching rules and
job release strategies are examined using simulation. Results highlight the importance of controlled re-
lease of jobs to the shop floor and the importance of differentiating between bottleneck and
non-bottleneck work centres for purpose of dispatching.
Keywords: Order Release; Dispatchi ng; Batch Split t ing
Workload Control (WLC) is a Production Planning and Con-
trol (PPC) approach specifically designed for the needs of the
make-to-order (MTO) industry and job shop manufacturing. It
aims at firmly controlling job flow times through the produc-
tion system by means of input/output control decisions towards
meeting the promised delivery dates.
Several WLC methods, varying in the degree of sophistica-
tion, have been described in the literature [1]. A common de-
nominator of these methods is the use of a pre-shop pool, where
the jobs wait for a release decision, and a release mechanism
[2]. The pre-shop pool can absorb fluctuations in the incoming
flow of jobs, reduce disturbances caused by order cancellations,
allow later ordering of raw materials and reduce the need to
expedite jobs on the shop floor. The release mechanism make it
possible to control the length of the queues on the shop floor,
reduce shop congestion and increase load balancing among
work centres, thus shortening and stabilising throughput times
Past research in the field of WLC, essentially simulation
based, often assumed that released batches (or jobs) proceed
through the different stages of processing without being split
([4] and [5]).
In contrast, this research investigates how WLC performs in
shops where batch splitting is applied. Batch splitting allows
released batches to be split into smaller sub-batches, which
proceed independently, so that processing of its operations at
work centres can overlap and its progress accelerated, as ob-
served by [6]. Ref [7] also observed that batch splitting has
great potential for helping improving due date performance.
Ref [8] examined the impact of batch splitting in shops with
varying flow dominance and concluded that flow shops are
more likely to benefit from batch splitting than job shops. Later,
[9] examined the performance of various release strategies in a
DBR (Drum-Buffer-Rope) environment. They found that sig-
nificant improvement in shop performance can be realized if
batch splitting is allowed.
The remainder of the paper is organized as follows. Section
II briefly presents the focus of this research work. Section III
outlines the simulation model and the experimental design be-
fore the simulation results are presented and discussed in Sec-
tion IV. Finally the concluding remarks and directions for fu-
ture research work are put forward in Section V.
Focus of This Res earch
No research is available in the field of WLC that investigates
how to take advantage of batch splitting for reducing delivery
times, while maintaining high delivery reliability. In response,
this research study investigates two release strategies, namely
immediate release and the periodic with intermediate pull re-
lease, and three dispatching strategies, assuming unbalanced
resource (machine) utilizations levels and thus the existence
protective capacity at non bottleneck resources. Experimenta-
tions are conducted for a general flow shop, which is usually
considered as having most in common with the real life job
shops [10].
We seek a better understanding of the impact of release and
dispatching strategies on the overlapping of operations and thus
on throughput times. Splitting a release batch into a number of
smaller sub-batches increases the probability of overlapping of
operations and allows reducing throughput times. However, this
is likely to require additional time being spent on setups, which
Copyright © 2012 SciRes.
may negatively affect performance, especially if these setups
are on the bottleneck resources. Thus overlapping of operations
and setup avoidance can be seen as competing objectives.
While protective capacity and setup times can be studied
across different levels, only one level is studied here because
the purpose of this paper is to provide exploratory results.
Simulation Study
A simulation study has been set up using Arena® software to
answer the research questions. During simulation experiments,
data were collected under steady-state. The length of each rep-
lication was 30000 time units with a warm-up period of 4000
time units. The average values of 100 independent replications
are presented as the result of one experiment. Common random
numbers were used as a variance reduction technique.
Simulation Model
We consider a six work centre general flow shop [12] with
two bottlenecks and a single machine per work centre. The
simulation model was kept simple to avoid interactions that
might inhibit the full understanding of the effects being studied.
As jobs arrive to the production system their due date, rout-
ings and operation times are identified. It is assumed that all
jobs are accepted and materials are available. As in previous
studies [11] due dates are set using the TWK rule, Due Date =
TNOW + c.TWK, where TNOW is the arrival time of the job, c
is a constant and TWK is the total work content of the job. The
value of c was set such that approximately 25% of the jobs
were tardy under immediate released and first-come-first-
served (FCFS) dispatching. This value was found to be suitable
to show the relative behaviour of control strategies.
Jobs inter-arrival times follow an exponential distribution,
with the number of operations per job drawn from a discrete
uniform distribution with a minimum of 1 and a maximum of 6.
Six types of jobs are considered, each of which with an equal
probability of being assigned to an arriving job. Released
batches or jobs are split into smaller equal size sub-batches,
which are then independently processed through the shop floor.
The number of sub-batches in each release batch is drawn from
a discrete uniform distribution with a minimum of 2 and a
maximum of 4. Sub-batches are moved from one work centre to
the next for processing without waiting for the entire job to be
processed at the earlier work centre and thus allowing succes-
sive operations of a job to be processed simultaneous.
On the shop floor capacities of machines remain constant
over time. Processing times were drawn from a truncated
2-Erlang distribution with a maximum that equals four times
the mean value. The mean processing time at the bottleneck
work centres was set to 1 time unit. The routings and process-
ing times ensures that the average utilization at bottleneck work
centre is 90% under FCFS dispatching and at the non-bottle-
neck work centres is 80% of the utilization of the bottlenecks
work centres. Each operation requires one specific work centre
and return visits to same machine are not allowed. The
setup-to-processing time ratio was set to 0.2 (20%). Setup times
were assumed to be deterministic.
Experimental Design and Parameters Settings
The experimental factors and simulated levels considered in
this study are summarised in Table 1. The release strategy was
Table 1.
Experimental factors and levels.
Experimental factors Si mulated levels
Job release strategy IMR PPR
Dispatching strategy S1 S2 S3
Worload norm levels Inf inity, 14, 11 .9, 10.1, 8.6, 7.3, 6.2, 5.3, 4.5, 3.8
tested at two levels and dispatching was tested at three levels.
These results in a full factorial design with 6, i.e. 2x3 combina-
tions of settings. Combinations involving the controlled release
of jobs have been run at 10 workload norm levels, in order to
generate performance curves. The resulting total number of
simulation experiments was 33.
Two relea se strate gies we re invest igat ed in the study , namely :
Immediate Release (IMR) and Periodic with intermediate Pull
Release (PPR) [5]. In the former, jobs are released into the shop
floor as they arrive, which means uncontrolled release of jobs
to the shop floor. In the latter, jobs are considered for release
accordingly to its urgency and released only if the resulting
workload does not exceed predefined workload norms. A
planned release date (PRD) is determined for each job in the
pool, by subtracting the planned throughput time of each work
centre in the routing of the job from the job’s due date. Jobs are
then selected for release according to the PRD. At fixed periods
of time the workload at work centres is computed and the deci-
sion to release one or more jobs from the pre-shop pool is taken.
Workload is accounted by the corrected aggregate load ap-
proach. The corrected aggregate load has shown to be a robust
and an effective approach, see [12]. Pull releases also may take
place between periodic releases, every time the workload of any
work centre falls to zero. In this case, only those jobs within the
pre-shop pool that have the first operation at the starving work
centres are considered for release. The selected job is not sub-
jected to workload norms.
Priority dispatching influences the pattern of batches pro-
gress through its processing stages on the shop floor. Three
dispatching strategies were considered in the study, namely:
S1: The earliest Planned operation Starting Time (PST)
rule is applied to all work centres;
S2: The Setup Oriented Planned operation Starting Time
(SOPST) rule is applied at the bottleneck work centres, whereas
the PST rule is applied at the non-bottleneck work centres;
S3: The SOPST rule is applied to all work centres.
Note that PST acts by giving priority to the jobs that become
most urgent at each work centre. It is a commonly used rule
within WLC (see e.g. [5]) and is focused on reducing the varia-
tion of the lateness across jobs. The PST of a job j at work cen-
tre v is determined as follows:
jv jw
= −
Where Tw is the planned throughput time at work centre w,
Sjv is the set of work centres in the remaining routing of j after
work centre v and dj is the due-date of job j.
SOPST was recently introduced by [5]. It scans the queue for
a job of the same type of that being processed. If no job is
found, the job with the shortest PST is selected.
Workload norms were tested at 10 levels of restriction in-
cluding infinity, tightness steps were of 85%. In addition to
Copyright © 2012 SciRes.
workload norms levels, WLC requires a number of other pa-
rameters to be specified for job release, namely [13]: planned
throughput times for each work centre, a release period length
and a time limit.
The planned throughput times Tw were obtained based on the
realised throughput times in preliminary simulation runs. These
runs also indicate that there is no important change in perform-
ance due to adjustments in Tw.
In all simulation experiments involving periodic release of
jobs to the shop floor the release period length was fixed at 1
time unit. This parameter defines the time interval between job
release activations and thus the release frequency.
A time limit is usually used to prevent jobs from being re-
leased too early. It allows defining the set of jobs in the
pre-shop pool that can be selected for release each time job
release is activated. In the experimentation the time limit was
set larger enough to avoid needlessly retaining jobs in the pool
and thus to avoid increasing system throughput times, see e.g.
Simulation Results
This section examines the results of the simulation study de-
scribed in the previous section. System performance is primar-
ily measured by two types of criteria: the ability to provide
shorter delivery times and the ability to deliver jobs on time.
Performance measures used with regard to the former are the
total throughput time (TTT), the release batch throughput time
(TRB), the sub-batches throughput time (TSB). Performance
measures with regard to the latter are percentage of tardy jobs
(Ptardy) and the standard deviation of the lateness (StD lateness).
TTT is the time a job (or batch) spends waiting in the pre-shop
pool plus the release batch throughput time TRB. This refers to
the time that elapses between batch release and batch comple-
tion. Note that with batch splitting a release batch is not com-
pleted until all sub-batches that belong to the release batch are
fully processed. TSB refers to the average throughput time a
sub-batch spends in the shop floor.
An overview of performance values, with 95% confidence
intervals, for dispatching strategies under immediate release is
presented in Table 2. Results can be summarised as follows:
Strategies S2 and S3 allows reducing throughput times,
TSB, TRB and TTT, relatively to strategy S1 (PST dispatching).
These are setup oriented rules focused on avoiding setups and
thus reducing machine utilisation rates, and therefore through-
put times. The former applies the SOPST rule at the bottleneck
work centres and the PST rule at the non-bottleneck work cen-
tres. The latter applies the SOPST rule to all work centres.
Table 2.
Performance results under immediate release.
Perfomance measure Strategy 1 Strategy 2 Strategy 3
TSB 10.4±0.13 8.6±0.07 8.4±0.06
TRB 11.0±0.13 9.3±0.07 9,0±0.06
TTT 11.0±0.13 9.3±0.07 9.0±0.06
Ptardy (%) 7.8±0.43 5.3±0.19 6.8±0.19
StD lateness 7.7±0.19 8.1±0.08 9.4±0.07
Strategies S2 and S3 also result in a lower percentage of
tardy orders when compared with S1, even if the SOPST rule
tends to increase the size of processing batches, and thus the
variation of the lateness across jobs as observed in Table 2.
The best overall dispatching strategy under immediate re-
lease is S2. It results in identical throughput times to that of
strategy S3, while ensuring the lowest percentage of tardy jobs,
i.e. about 5.3%. SOPTS minimizes the time spent on setups at
the bottleneck work centre, while PST allows incurring in addi-
tional setups at the non-bottleneck work centres, which have
additional capacity, by giving priority to jobs that become most
Note that once IMR is applied, jobs do not wait in a pre-shop
pool and thus the TTT and TRB are equal.
Next we investigate the influence of controlled job release.
Figures 1 show results of the periodic with intermediate pull
5,5 6,5 7,58,59,5 10,5 11,5
Tardy Orders (%)
Batch Throughput Time
5,5 6,5 7,5 8,59,510,5 11,5
Total Throughput Time
Batch Throughput Time
5,5 6,5 7,5 8,5 9,510,511,5
StD Lateness
Batch Throughput Time
Figure 1.
Simulation results: (a) percentage of tard y jobs; (b) total thoughput time
and (c) standard deviation of lateness.
Copyright © 2012 SciRes.
release (PPR) method. A logistic performance curve was de-
veloped for each dispatching strategy, S1 to S3. Results are
compared with IMR.
The percentage of tardy jobs, total throughput time and the
standard deviation of the lateness are plotted as a function of
the average throughput time of release batches. A marker on a
curve is the result of simulating the release method at a specific
workload norm level. The right-hand mark on each curve refers
to an experiment with infinite workload norms, i.e. meaning
periodic unrestricted release. Tighter norms result in shorter
release batch throughput times. Thus, the horizontal axis on
each figure reflects the norm tightness level. Results can be
summarised as fol l ow s:
From this curves it can be observed that controlling order
release accordingly to the PPR method significantly reduces the
percentage of tardy orders, relatively to IMR, even if it results
in a high standard deviation of lateness, especially for tight
workload norms. This essentially results from delaying orders
in the pre-shop pool before release when workload norms are
The same as under IMR, dispatching strategy S2 results
in the lowest percentage of tardy jobs when PPR is in place,
particularly for tight workload norms. Likewise, strategy S1
also shows the worst performance for the percentage of tardy
orders, but only for infinite or extremely loose workload norms.
The best control strategy, resulting in the lowest percent-
age of tardy orders with the lowest batch throughput time, con-
sists of combining PPR release with SOPST dispatching at the
bottleneck work centre and PST dispatching at the
non-bottleneck work centres, i.e. S2.
This paper presents the results of a simulation study of re-
leasing and dispatching strategies in a general flow shop with
unbalanced resource utilizations.
Results highlight the importance of differentiating between
bottleneck and non-bottleneck work centres for purpose of dis-
patching. Dispatching strategies that tend to increase the size of
processing batches (i.e. setup oriented) should be applied at the
bottlenecks work centre, while dispatching strategies that sup-
port the overlapping of successive operations of a job, and that
may result in additional setups, should be applied at the
non-bottleneck work centres. These work centres by definition
have excess of capacity, which may be used to deal with the
additional setups.
Results also indicate that controlled release of order based on
the periodic with intermediate pull release method performs
better than immediate release for both the percentage of tardy
orders and throughput times.
Additional research is needed involving other shop configu-
rations to increase understanding of the workload control con-
cept in production systems with unbalanced resource utiliza-
tions and batch splitting. In particular the exploration of bottle-
necks at different routing positions shall be evaluated in future
This work had the financial support of FCT- Fundação para a
Ciência e Tecnologia of Portugal under the project PEst-OE/
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