Keywords:

scheduling,

job shop,

Bio Robot,

blood test

Original Report

Development of an ImprovedScheduling Algorithm for Lab TestOperations on a Small-Size BioRobot Platform

*CoEng300Kor

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doi

Seung Hoon Shin,1 Byung June Choi,1 Sung Moo Ryew,2 Jung Woo Kim,2 Dae Shick Kim,3

Wan Kyun Chung,4 Hyouk Ryeol Choi,1 and Ja Choon Koo1*1Sungkyunkwan University, Suwon, Korea

2KNR Systems, Yongin, Korea3Samsung Medical Center, School of Medicine, Sungkyunkwan University, Seoul, Korea

4Pohang University of Science and Technology, Pohang, Korea

Blood tests are one of the core processes in the clinical

laboratory test field. In hospitals, an automated

process called total laboratory automation (TLA), which

relies on a set of sophisticated equipment, is normally

adopted for the tests. Noting that the TLA system

typically has a large footprint and requires a significant

amount of power, slim, and easy-to-move blood test

equipment is necessary for some specific demands such as

emergency rooms or small-size local clinics. Although

various portable blood test systems are introduced and

popularly used in many labs, the test processes of these

systems are not usually flexible. In the present work,

a new scheduling algorithm called reduced idle time (RIT)

is developed for a small-scale portable Bio Robot

platform. The RIT can successfully handle a series of

components of the Bio Robot such as a liquid handler, six

incubators, a newly developed spectrophotometer, and

a robot arm. It also shows an enhanced effectiveness in

terms of the testing time reduction when it is tested with

the developed robot platform. Additionally, the RIT

rrespondence: Ja Choon Koo, Ph.D., School of Mechanicalineering, College of Engineering, Sungkyunkwan University,

Chunchun-Dong, Jangan-Gu, Suwon 440-746, Republic ofea; Phone: þ82.31.290.7454; E-mail: jckoo@skku.edu

5-5535/$36.00

yright �c 2010 by The Association for Laboratory Automation

:10.1016/j.jala.2009.02.003

shows a fairly flexible capability to accommodate new

incoming samples that might interrupt an on-going process

and requires an immediate rescheduling. ( JALA

2010;15:15–24)

INTRODUCTION

Today, fully automated laboratory analyzers are oneof the critical elements of the health care industry.Many labs in hospitals currently have either a modu-lar preanalytical with an analytical system or a totallaboratory automation (TLA) system for clinicalchemistry immunology tests.1e3 Instruments thatare normally adopted for the preanalytical systemsmight be a sample input line, a centrifuge, a conveyorline transporting sample, a bar code reader, and a de-capper. Also, the instruments that are used in the an-alytical system are an aliquotter, an incubator, anda detector.

As a process of the tests consists of the preanalyt-ical process and the analytical process, samples arenormally analyzed in an automated analyzer afterthe preanalytical process.

When tests are performed using an automatedlaboratory analyzer, each test process should be car-ried out through a distinct and unique routine. Forexample, a typical test could be started when an ali-quotter dispenses blood samples on a microplate andthen adds reagent onto the plate. Then after reacting

JALA February 2010 15

Figure 1. A turntable type small-scale bio test machine.

Original Report

in an incubator, the aliquotter dispenses the second reagentonto the microplate.

Eventually, the spectrophotometer detects the absorbanceof the sample after reacting at the proper incubation

Figure 2. Basic algorithm: shortest processing time.

16 JALA February 2010

temperature. Although this might be a typical test process, itis not definitely a universal routine that could be used for allof the blood tests. Therefore, determination of a properprocess for each unique test is necessary and a well-definedscheduling algorithm is required for this purpose.4

In the present article, a newmodified scheduling algorithm ispresented, which is formulated with a job shop method. Thisalgorithm can be applied as a test scheduler for small-scale por-table lab test equipment. The proposed method is tested withnewly developed portable lab test equipment and the test resultsare analyzed with discussions. The presented method providesan enhanced test throughput on a small-scale test machinecompared to previous schedulers.

JOB SHOP PROBLEM

A job scheduling is required for the operation of multideviceequipment in many industrial applications. Industrial prod-ucts such as automobiles, consumer electronics, or pharma-ceutical products are often manufactured through a serialor parallel assembly line, whereas some others like petroleumare manufactured by a continuous process.

Table 1. The process of the ALT clinical test9

ALT

1. Incubate substrate solution after mixing L-alanine 0.5 molþ Tris

0.1 mol. with robot arm

2. Dispense sample 200 mL

3. Incubate 1 min

4. Detect absorbance every 30 s at wavelength 340 nm for 2w3 min

Original Report

A definition of job scheduling consists of planning andprioritizing activities that need to be performed by a systemof equipment so that jobs are lined up with a proper order ofoperation. Job scheduling is therefore a tool that optimizesthe usage of available resources for the accomplishment ofa certain task. A well-coordinated job scheduling enhancesefficiency, maximizes capacity utilization, reduces operationtime, and consequently maximizes profit.

For an automated laboratory test in a hospital, the prin-ciple objective of the incorporated scheduling might be a re-duction of test cycle time that is required for completion ofassigned jobs. Because the throughput of a test system canbe improved only through the reduction of process time,the adoption of a well-defined scheduling algorithm is criticalfor the overall process improvement. As mentioned in thepresent work, a scheduling algorithm is developed and testedwith a small-scale bio test platform. The design concept ofthe Bio Robotic lab test system will be a reference systemfor the present development that is depicted in Figure 1.The system consists of a robot arm that drives a liquid han-dler for dispensing samples and reagent, a reagent container,microplates, pipettes, sample tracks, incubators, and a pho-tometry scanner.

The test procedure of each individual job is unique. Eachstep of a procedure is handled by an independent machine ora device of the system. Therefore, each test step is regarded asa job because it is unique and independent. In other words,independent n jobs should be processed according to a prede-termined procedure using m machines for the minimizationof total processing time. Solutions of this problem have beenstudied extensively in the operational research field and thisproblem is normally referred to as a ‘‘job shop’’ problem.

Table 2. Array A of input list

Ji Oi Mi Pt (s) Pt0 Pt1 Arg1 (nm)

1 1 1 20 0 0 A

1 2 2 30 0 0

1 3 1 20 0 0

1 4 2 60 0 0

1 5 3 180 0 0 340

1 6 4 5 0 0

Ji¼ Job Index; Mi¼Machine Index; Pt0¼ process starting time; Arg1¼ reagent 1; Arg3¼ reagent 2; Arfinishing time; Arg2¼ amount of reagent 1; Arg4¼ amount of reagent 2; Agr6¼ amount of sample; B

The order of individual jobs may be independent to eachother and unique, although the independent order mightbe fixed. For n jobs and m machine scheduling problem,there are (n1)! (n2)! . (nm)! possible sequences in theory,where nk is the number of operations to be performed onmachine k; although all of them are not feasible. The bestjob sequence must satisfy the following conditions: (1) itmust be technologically feasible (i.e., satisfy the machineprecedence constraints) and (2) it must be optimized for ef-fectiveness. Because an evaluation of all possible combina-tions is an impossible task even for a moderate sizeproblem, many heuristic rules have been developed by var-ious researchers to determine the priority by which a jobshould be processed.5,6

JOB SHOP SCHEDULING ALGORITHM WITH LOADING

RULES AND HEURISTIC RULES

The popular methods for the job shop scheduling problemare loading rules, heuristic rules, integer linear programming,complete enumeration, sampling methods, and learning tech-niques.7,8 The loading rule and the heuristic rule are reviewedhere because those algorithms are used for the present work.The loading rule progresses by selecting the next process ofthe individual machine. The selected processes have to be fea-sible for the fixed sequence of tests and have to be finishedwith the least amount of idle time for each machine. If manyprocesses are to be done, the job sequence is to be determinedby the so-called shortest processing time (SPT), which is oneof the heuristic rules. The SPT is usually regarded as the ba-sic algorithm and has been explained in Figure 2. The SPTnormally shows fair performance when a job requires theuse of multiple machines.

In Figure 2, A is a two-dimensional array that stores inputlists, M is a three-dimensional array containing informationabout machines that should be used to organize array A, J isalso a three-dimensional array that holds the details aboutjobs that should be performed for A, B is a null array thathas the same dimension as M, and S is a two-dimensional ar-ray that can store one page of a three-dimensional array. Forexample, a test alanine aminotransferase (ALT) is normallyperformed with the sequence provided in Table 1 and thecorresponding input list is given in Table 2 that should be

Arg2 (mL) Arg3 Arg4 (mL) Arg5 Arg6 (mL)

0.5 B 0.1

1 0.2

g5¼ sample (blood); A¼ L-alanine; Oi¼Operation Index; Pt¼ processing time; Pt1¼ processing¼ Tris.

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Figure 3. Gantt chart with 10 tests scheduled by the basicalgorithm.

Original Report

stored in array A. As each row represents a single operation,three-dimensional arrays M and J are determined from thisinput list.

Each page of array M contains information about jobsthat should be performed on a machine and the jobs aresorted according to the required processing time. Meanwhile,each page of array J contains information about operationsthat require the same job. As mentioned, array B is the samesize as M, and it is initialized with all null values. Then, thealgorithm selects feasible operations from array M by exam-ining the operation index and processing time provided byarray J. The created operations are stored into a two-dimen-sional array S. Then by inspecting S to determine if there isany operation that produces idle time for a machine, the se-quence is to be recalculated to minimize the idling periods.The rows of array B are changed for the SPT operations,meanwhile the corresponding row of array M is set to zero.This process should be repeated until all the arguments ofarray M are zero.

Although the SPT may provide the shortest job schedulefor simple cases, this method cannot be applied to a case suchthat a single job uses a particular machine more than twice.To describe the limitations, 10 randomly selected clinicaltests are scheduled by this algorithm and the results are pre-sented in Figure 3. In the figure, a Gantt chart shows thatthere is a significant amount of idle time as marked witha dotted circle. The idling time slots can be of course elimi-nated with modification of the algorithm and many develop-ments are even available in textbooks, although there aresome arguments on the efficiency of these methods. In the

Figure 4. The Gantt chart of the basic algorithm.

18 JALA February 2010

present work, a newly developed algorithm named the re-duced idle time (RIT) is introduced and tested for the reduc-tion of total processing time.

RIT ALGORITHM

An exemplary case shown in Figure 4 explains the limitationsof the SPT. The algorithm distributes jobs to correspondingmachines using information stored in array M. When a situ-ation happens at the middle of a scheduling process such thatjob 421 is to be inserted, the only option for the SPT is locat-ing the job in slot (c). Regarding job number 421, 4 standsfor job number 4, 2 is for process number 2 in job 4, and 1represents machine number 1 that is used for process 2 ofjob 4. Although job 421 can be allocated in either slot (a)or slot (b) to minimize the idling time, the SPT routinely as-signs the job in (c) because a job uses a particular machinemore than once.

Noting the critical drawback of the SPT algorithm,Figure 5shows a new algorithm called the RIT that has been developedand constitutes a key contribution of this paper.

EVALUATION

To evaluate the performance of the proposed RIT algorithm,the total completion time and tardiness of the algorithm werecompared with two other methods. These comparativemethods are the basic algorithm (SPT) mentioned beforeand the modified shifting bottleneck heuristic (MODSB) thatis formulated by a network approach.

A set of 20 samples that requires 10 jobs and 10 machines(10� 10), where each job uses a particular machine onlyonce, is assigned to the basic algorithm, MODSB, andRIT, respectively. The results are shown in Figure 6. Fromthe test in which a job uses a particular machine only once,the RIT and the MODSB show better performance overthe basic algorithm although performance improvement isnot significant.

However, in actual clinical tests a job may use a particularmachine multiple times, meaning the test cases should also toensure a fair evaluation. In the next test case, a set of 20 sam-ples with randomly selected 50� 50 cases are given to the pro-posed RIT and the basic algorithm. Note that each job usesa machine twice. The MODSBmethod is not used for this testbecause the network method has a limitation on the handlingof cases that require multiple usage of a single machine.

The comparative results are shown in Figure 7 and fromthese results, a significant performance improvement of theRIT over the basic method can be seen.

RESCHEDULING

In the actual clinical tests, a situation for adding a new ur-gent test frequently happens while other tests are being per-formed. In this situation, the on-going job schedule shouldbe modified to assign a higher priority to the emergency in-coming test while minimizing influence on the current tests.

Figure 5. Reduced idle time method (a left shifting method).

Figure 6. Comparison of the reduced idle time versus modified shifting bottleneck heuristic and basic algorithm.

JALA February 2010 19

Original Report

Figure 7. Comparison of the reduced idle time and basic algorithm about 20 random test samples using a machine more than twice.

Figure 8. The example for rescheduling.

20 JALA February 2010

Original Report

Figure 9. Adding a new test.

Table 3. Specification of the Bio Robot system

Test throughput 240 tests/h

Capacity of sample tray 7-mL tube, 21 samples

Micropipette for dispensing sample 20 mL, 0.5 mL resolution

Capacity of reagent tray 40 mL, tube, 70 reagents

Micropipette for dispensing

reagent

1 mL, 1 mL resolution

Temperature of incubator 37 �C, 1 �C resolution

Robot exterior dimensions 800� 800� 1500 (mm)

Original Report

The proposed RIT algorithm provides fairly robust re-scheduling capabilities thanks to the loading rule that is a ba-sis of the RIT formulation. The first step of the RITrescheduling starts by rearranging information of the B, M,and J arrays by reviewing tests that have been finished at thatmoment. Then, the new test is inserted in the first row ofarray M and J. Finally, the RIT algorithm is to be appliedfor a new schedule. For example in Figure 8, tests 412,421, and 433 are newly added at time ta, while a scheduledoperation of a current procedure is going through that whichis shown in Figure 8a. First, the RIT rescheduling has tocheck if any on-going test steps are under operation becausethe current test step should not be interrupted for the newincoming test. In Figure 8b, the RIT has sorted out the on-going process that should maintain their original schedule.Then, arrays M and B are rearranged as shown in Figure 8c.At this moment, the new tests are assigned at the first row

Figure 10. A portable Bio Robot system for automated clinicaltests.

because they are urgent and have a higher priority. Therescheduled sequence is shown in Figure 8d.

To verify the RIT rescheduling capability, a test used forthe previous comparative study is reconsidered at this mo-ment. The test consists of 10� 10 cases that use a machinetwice. A new test is added at certain time during the executionof the 10� 10 tests. The new test is added at a time of about50 s after initiation of the test. The ideal completing timeof the new test is 119 s without delay of the test. The resultin Figure 9 shows that the rescheduling is properly carried out.

EXPERIMENT

Portable Bio Test Robot System

For the actual functional test of the proposed RIT, a porta-ble BioRobot system pictured in Figure 10 is used and its tech-nical specifications are provided in Table 3. The Bio Robotsystem has a liquid handler, incubators, insertion module,removal module, elevator module, and spectrophotometer.

The liquid handler that is manipulated with a four-axis ro-botic arm dispenses reagents and blood samples. The elevator,insertion, and removal modules are equipped for the handlingofmicroplates. Like as with other routine lab tests, blood sam-ples and reagents are reacted in the incubator. The incubatedmicroplate is taken out from incubator by the removalmodule.

For scheduling the clinical tests with this system, a liquidhandler, six incubators, removal module, and spectropho-tometer are considered to be independent machines.

These machines are controlled by a stand-alone controllerthat is communicating to a personal computer through a se-rial communication protocol. Once a user selects a test anddesignates blood samples for the test from the given graphicuser interface (GUI) environment of the system, the RITexports the appropriate schedule, where it is converted andfed to the controller to operate the corresponding machines.The system interface is shown in Figure 11. The system soft-ware is programmed with National Instruments Labview.Figure 12 shows an example job schedule and its correspond-ing machines.

Hardware Verification Results

In this section, the RIT algorithm will be tested with theintroduced portable Bio Robot hardware. The verification

JALA February 2010 21

Figure 11. User interface for the Bio Robot system.

Figure 12. Inspection procedure in the scheduler.

22 JALA February 2010

Original Report

Figure 13. The result of the scheduling (20 tests).

Original Report

is organizedwith 20 tests and the results are shown inFigure 13.Also, the rescheduling capabilities are tested and the results aregiven in Figure 14. The test shows reliability of the proposedRIT algorithm and its rescheduling capability.

CONCLUSION

In this article, a new scheduling algorithm for clinical tests isdeveloped and tested with a portable Bio Robot system. Al-though in general the scheduling problem of clinical testsmay be carried out with job shop problem routines, the

performance may not be very effective for a certain testdue to many constraints such as multiple usage of a particularmachine. However, the proposed RIT algorithm, of whicha left shifting algorithm is the core concept, shows superiorperformance for the handling of cases where a single job usesa certain machine multiple times. A comparative study hasbeen performed for the verification of this algorithm’s supe-riority, which is applied to an actual hardware operation us-ing a Bio Robot platform. In the actual hardware test, thedeveloped RIT algorithm is proven to be more effective thanother previous methods.

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Figure 14. The result of the rescheduling (9þ 1 tests).

Original Report

ACKNOWLEDGMENT

This workwas supported by ‘‘Development of Intelligent Robot Technologies

for Laboratory Medicine by Applying Biotechnology’’ under the Develop-

ment of Next-Generation New Technology program and ‘‘Workforce Devel-

opment Program in Strategic Technology of Korea Institute for

Advancement inTechnology’’ of theKoreanMinistry ofCommerce, Industry,

and Energy.

Competing Interests Statement: The authors certify that all financial and

material support for this research and work are clearly identified in the

manuscript.

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