SILAB

A System to Support Experiments in the Electric Power Research Center Labs

Henrique Burd

, Wagner Duboc

, Marcio Antelio

2,3

, Sergio Assis Rodrigues

, Allan Freitas Girão

Jacson Hwang

, Rodrigo Pereira dos Santos

and Jano Moreira de Souza

Electric Power Research Center (CEPEL), Rio De Janeiro, Brazil

COPPE/UFRJ, Federal University of Rio de Janeiro, 21945-970, Rio de Janeiro, Brazil

Federal Center for Technological Education Celso Suckow da Fonseca (CEFET/RJ), Rio de Janeiro, Brazil

Keywords: Information Systems, Energy Domain, e-Gov, Experimental Process, Workflow.

Abstract: Companies, research centers, and universities are increasingly keeping in contact over time. Especially after

Internet, the “Web Era” has contributed to a dynamic market as well as to a critical relation between

management and engineering in industry. Thus, research centers can help companies in supporting and

improving their activities and processes through innovation partnerships. In Brazil, the Research Center for

Energy (CEPEL) is exploring information systems applied to its modernization. In this sense, this paper

presents SILAB, a system to manage actions of clients and laboratories during processes of provision test

and certification of equipment. SILAB was developed from an experience based on the govern-university

partnership. The main focus is to support standards, transparence and productivity in a domain-driven

workflow. Some experiences collected from SILAB’s stakeholders are also discussed.

1 INTRODUCTION

The relation between companies and universities

depends on innovation policies in order to promote

competitive strategies for the former (SOFTEX,

2009). In addition, it stimulates the development of

new researches for the latter. The dynamics in this

relation are created due to a more competitive

market since companies look for new knowledge

produced by universities. An example is the

Association for Brazilian Software Excellence

Promotion (SOFTEX) whose objectives are to

increase the participation of Brazilian Information

Technology (IT) companies in the market and

support the future of Brazilian software exportation

driven by quality standards (SOFTEX, 2007).

This way, the interactions among those entities

can be described in different ways, such as: (i)

producing knowledge related to company’s

technologies (Klevorick et al., 1995), (ii) training

experts to work with innovative processes (Pavitt,

1984; Rosenberg, 1992); (iii) elaborating new

scientific methods (Rosenberg, 1992); and (iv)

creating companies named spin-offs lead by scholars

(Stankiewicz, 1994); (Etzkowitz, 1999). Moreover,

there are many initiatives related to the mapping of

scientific research and modernization of companies.

For example, investigation of papers cited in patents

(Narin et al., 1997), research studies related to

papers published by companies (Godin, 1996), and

surveys and questionnaires applied to firms

(Mansfield, 1991); (Klevorick et al., 1995); (Cohen

et al., 2002) and scholars (Meyer-Kramer and

Schmoch, 1998); (Schartinger et al., 2001; 2002).

In relation to Brazilian electric sector, Research

Center for Energy (CEPEL) promotes several

initiatives in modern laboratories to evolve this

sector and enable Brazilian electric firms. This

center is a part of a Brazilian company named

ELETROBRAS (ELETROBRAS, 2013) that

supports researches in energy sectors such as

described in (Pereira, 1995), and also participates in

technology policies (Saravia, 2005). Since there is a

concern related to the development and use of

information systems (ISs), CEPEL has investing in

improving its services through the processes

automation via software solutions. For instance,

Oliveira (2010) uses simulation tools for conducting

a comparative analysis related to the performance of

current processes and redesigning them.

In order to improve the laboratory processes, this

paper discusses a system called Information System

287

Burd H., Duboc W., Antelio M., Assis Rodrigues S., Freitas Girão A., Hwang J., Pereira dos Santos R. and Moreira de Souza J..

SILAB - A System to Support Experiments in the Electric Power Research Center Labs.

DOI: 10.5220/0004942602870292

In Proceedings of the 16th International Conference on Enterprise Information Systems (ICEIS-2014), pages 287-292

ISBN: 978-989-758-027-7

 2014 SCITEPRESS (Science and Technology Publications, Lda.)

of Laboratories (SILAB). It has been developed

through a partnership between CEPEL and the

Computer Science and Systems Engineering School

(PESC/COPPE) of a Brazilian public university

(Federal University of Rio de Janeiro). The goal is to

manage clients and laboratories’ actions during the

processes of executing tests and certifying

equipment (accomplished by the former). It aims at

making the work of laboratory teams more efficient,

providing appropriated information to managers and

improving invoice payment services. SILAB is a

transparent environment where clients make orders

and follow laboratory processes related to tests and

certifications, and also provide evaluation indicators

of laboratory processes.

This paper is organized as follows: Section 2

summarizes the background related to IS-based

scientific processes and experimentation; Section 3

presents an overview of SILAB and its

requirements, architecture and goals; Section 4

present the results of a survey driven by SILAB

features; and Section 5 concludes the paper,

discusses lessons learned and points out future work.

2 BACKGROUND

Nowadays, ISs have been considered complex and

fundamental artifacts for the modern societies. ISs

are in all knowledge domains such as Education and

Experimentation and are strongly applied to Web

content management. This requires well-known and

solid infrastructures, quality in software solutions

and developer-oriented platforms (Stefanuto et al.,

2011). On the other hand, ISs should consider both

social and automated subsystems as happening in

some IS categories, for example (O’Brien, Marakas,

2005): (i) groupware: IS that supports cooperation

/collaboration; (ii) knowledge management: IS that

supports information/knowledge storage/retrieval;

and (iii) workflow: IS that supports planning and

control of work tasks, activities and products.

IS focused on Web content management joins

the characteristics of the three mentioned IS

categories. Initially, these systems were labeled as

Internet-based portals and have common

requirements such as download and upload speed,

support big data (i.e., data volume and accesses),

easy communication, and tasks/artifacts coordination

etc. (O’Brien and Marakas, 2005). Especially in

experimentation domain in research laboratories, the

empirical paradigm involves the collection and

analysis of data and evidences that can be used to

characterize, evaluate and show relations among

technologies, practices, and experiences around a

fact or artifact (Biolchini et al., 2007). This way, IS-

supported empirical processes should be developed

to control and manage the experiments lifecycle as

well as their roles, activities and products.

Therefore, empirical results can compose a body

of knowledge over time (Basili et al., 1999), i.e.,

providing a base to accepted and well-formed

theories about some object of study. The empirical

studies allow theories to be formulated, tested, and

validated, evolving an experience report to a status

of evidence (or not). Evidences are generated from

characterizing, assessing, predicting, controlling,

and improving products, processes, and theories. On

the other hand, experiences can explore these studies

towards the continuous improvement.

According to Basili et al., (1999), the central

pillar is based on the main elements of an

experiment: (i) variables correspond to the inputs

(independent variables) and outputs (dependent

variables) of an empirical study; (ii) objects are a

target used to verify the empirical study’s cause-

effect relationship; (iii) participants represent the

individuals selected from the population to

participate in an empirical study; (iv) context

consists in the conditions which the empirical study

is done, and it can be characterized through the place

(in vivo, in vitro, in-virtuo, and in-silico); (v)

hypotheses correspond to theories being verified;

and (vi) empirical study project defines the

empirical study design (e.g., time, schedule, objects

and participants).

These experiments can be associated to scientific

workflows. According to Deelman and Gil (2006),

the concepts of workflow have recently been applied

to the automated large-scale science (or e-Science),

coining the term “scientific workflow”. The

scientific work is based on conducting experiments;

therefore, the workflow system should allow the

same information to be shown at various levels of

abstraction, depending on who is using the system.

Barker and Hemert (2008) discuss that the

elements of the workflow should be in the context of

the appropriate scientific domain and allow the

scientist to validate a hypothesis. The validation of

scientific hypotheses depends on experimental data,

and scientific workflow tends to have an execution

model that is dataflow-oriented. This is an essential

feature which makes business and scientific

workflows different. The former are based on the

control-flow of patterns and events, and workflows

in the scientific community involve the exchange

and analysis of large quantities of data among

distributed repositories. Scientists will have to

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schedule and fund the use of expensive resources,

and then systems that support them will be robust

and dependable. In addition, they should support

incremental workflow construction and the output of

workflows or themselves can be used as a basis for

future research.

Finally, considering empirical processes related

to the interaction among industry and research

centers, the management pillar should be

accomplished through a workflow system in order to

treat each experiment as a project. Scope, time, cost,

human resources, laboratory, machines, materials

and methods represent some aspects that must be

carefully treated by an IS for this domain. Since the

industry has lead with real objects and needs that can

have a significant impact at the society, these aspects

should be planned and monitored over time.

3 SILAB

From the reformulation of the Brazilian electric

sector in 2003, CEPEL back to its original objective

of working which research lines, supporting the

Brazilian electric companies. According to Burd

(2005), SILAB is presented as a system that was

initially developed to meet the requirements of

commercial proposals, approval of customers in

accordance with these proposals and documentation

of laboratory services. Nowadays, the business

requirement became more complex. Its

functionalities are divided in three main cycles as

presented in next sections.

3.1 Customer Cycle

The goal of this cycle is to manage all processes that

involve national and foreign customer. It consists of

the following modules: Order, Proposal, Company

and Invoicing. Order allows the research center

employees to manage customer orders. They are

registered by customers through an external access

module built directly to them. After their login, they

have access to an environment where they can fill

out and track their order states over time. Initially,

the employee receives notification of new orders

registered at SILAB. An order can present many

statuses depending on customer goals. After an

initial reading, it will be rejected if they do not meet

the purposes of the existing laboratories. If it does

not contemplate all initial requirements, a

negotiation among them is opened in order to clarify

information. They are forwarded to the analysis

phase when all initial requirements are met.

Additionally, this module supports a negotiation on

the price estimates.

In the analysis phase, the orders are studied in

more details and can also be rejected. They can

involve activities related to one or more laboratories,

and then they can be independently analyzed for

different ones. If all requirements are met, this

request becomes a proposal, i.e., an initial trade

agreement among the research center and their

customers can suffer changes over time. Besides, the

employees themselves can act as customers and

make internal orders. This event occurs when

instruments used by the laboratories need to be

calibrated outside.

Proposal is responsible for managing all states of

commercial proposal until they are accepted by the

client, initiating the laboratory activities. Firstly,

during the editing phase, this proposal is filled with

both activities that will be performed and the

quantity of equipment expected by a laboratory

(according to the request). After this phase, it is

forwarded to approval by the superiors. Also, after

successive and positive evaluations by them, the

commercial proposal is forwarded to the customer.

When it is accepted by him, activities described in

this proposal are performed by the involved

laboratory and the system tracks its history. It shows

all the proposal phases in different laboratory

accounts (responsible, observations, date, situation).

Besides, the order history that originated this

proposal is presented. The states showed in Proposal

and Order history describe the process flow from the

order editing to the proposal conclusion.

Company is responsible for managing customer

data. A company has three states: inactive, active

and pendent. The pendent state happens when the

company’s data are not validated yet. When data are

validated against norms based on Web services, the

state is active at SILAB. The validation process

includes applying security criteria, such as fiscal

situation or delinquency. If any data is incorrect or

incomplete, the state will be inactive. Only active

companies can make orders. To fill out an order, the

company contact must have permission to do this,

and then its data are validated too. Finally, the

payments of values described in the commercial

proposals are made through Invoice.

3.2 Laboratory Cycle

According to Deelman et al., (2009), scientific

workflow can be defined as formal specification of

scientific processes representing the steps which will

be performed by a given experiment. These steps are

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usually associated to the data collection, analysis,

and visualization. They are manually managed, or

supported by scientific workflow management

systems through executable artifacts (i.e., programs,

services and scripts).

SILAB supports the execution of the scientific

workflow during the test activities. In this phase,

processes are related to conduct different electric

experiments; to obtain high quality data; to analyze

them according to the business requirement; and to

generate a final report about them. This workflow

should be reused, evolved and shared with other

scientists in the field, as well as it must be fully

reproducible. In order to support this, SILAB

provides information about experiments. For

example, it indicates the origin of the data, how it

was modified, and which components and parameter

settings were used to execute tests. This will allow

other scientists to execute the experiment again in

order to confirm the results.

This cycle is composed by following modules:

Equipment, Test, Calibration, and Protocol. The last

one represents protocols for different types of

documents applied to SILAB. Equipment follows

this object from its entrance in the research center

(receive process) to its exit (devolution process),

passing by several tests in different laboratories. Test

is responsible for documenting all results obtained

during test phase in a specific laboratory. Each test

has its own data and they are verified by a reviewer

– this employee is not the same one that executed

the test. In addition, different reports are generated

and they are revised. This system has a revision

module that maps each data edition to different

revisions. An important process during the test phase

is Calibration, where all information related to the

instruments used during the tests is documented.

Figure 1: Revision process at SILAB.

The Figure 1 represents the cycle revision

process after executing tests or certifications. First of

all, the test data can be edited since it can be

repeated to confirm the expected result (new

version). When it is finished, these test data are

reviewed by other researcher. After reviewing a test

set, they cannot be altered and a report is generated

and associated to them. It is composed by its data

such as conclusions and observations, besides test

data previously mentioned. This report is on editing

state and it can be modified by a research that has

permission for doing this. After all changes, this

report is forwarded to another researcher to be

evaluated. If a report is evaluated and approved, it

will not be altered anymore (final version). This fact

determines a revision cycle is finished. In each new

cycle, all data changes in tests/reports are registered

and informed to the customers in the final report.

3.3 Maintenance Cycle

This cycle involves all modules related to the

research center’s employee information, such as

permissions, accounts and laboratories, besides their

agenda describing the laboratory activities. SILAB

offers different user profiles to access the system. In

relation to the safety, all users’ events in the system

are registered and classified according to certain

criteria based on their roles. The whole process

related to an order and a respective proposal is

mapped. This information about who analyses order

requirements, dates about state changes, period of

occupying laboratories, time of executing tests and

time of elaborating reports are registered and

represent by a timeline. The system also offers a

module responsible for generating process indicators

to knowledge experts.

3.4 Architecture

The architecture of SILAB is composed by a Web

system, a mobile system, Web services, an e-mail

server and databases (Figure 2).

Figure 2: SILAB architecture.

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The Web system communicates with SILAB

database to access information about the laboratory

and customer processes. All financial information

such as invoice and payments are in another

databases. The financial and SILAB data are shared

with other systems. SILAB have a mobile

component responsible for managing receiving and

delivering of equipment. Its users are notified by the

e-mail server about all changes in the processes

states during executions.

4 SURVEY

The objective of this survey is to evaluate the

characteristics of this system in order to verify the

usability and effectiveness of SILAB considering its

strong and weak points. This study will contemplate

two types of stakeholders: research center analysts

and clients (i.e., companies). The set of analysts are

compost by three stakeholders: managers (a

department director), researchers (an electrical

engineer) and general staff (a technician and a

secretary). This survey is divided into three parts: (i)

evaluation of general features, (ii) evaluation of

information; and (iii) evaluation of the process. The

results were aggregated through applying average.

Table 1 shows the results about general

evaluation of the system. In this part, the participants

answered questions about the system and its

influences to the reality of the company, ease of

access, interface and performance. It can be realized

that the strongest feature of SILAB is the report

generation, since this is important for managers,

researchers and customers. On the other hand, some

aspects of interface should be improved and a new

project to evolve the system as a whole is starting.

Table 1: General evaluation.

Poor

(%)

Fair

(%)

Satisfactory

(%)

Excellent

(%)

Reality 5 21 53 21

Accessibility 0 16 47 37

Interface 10 21 32 37

Performance 5 21 63 11

Reports 5 16 32 47

Table 2 shows the results about information

evaluation. At this stage, the participants answered

questions about availability of information,

understandable format and relevance. As observed,

the participants were satisfied with information

provided by SILAB, especially considering its

relevance to the management of the experiments.

However, some aspects related to the format of

information should be defined in a better way.

Table 2: Information evaluation.

Poor

(%)

Fair

(%)

Satisfactory

(%)

Excellent

(%)

Relevance 0 11 37 53

Format 11 11 53 26

Availability 5 11 47 37

Finally, Table 3 shows the results related to the

process standardization, productivity of employees

and the transparency of processes executed in the

system, considering the participants’ point of view.

Again, all participants mentioned that their tasks and

activities are easier after the SILAB deployment,

highlight productivity and transparency. Aspects

related to standardization are being investigated

since it is more complicated. One reason is the

different types of customers and partners and an

initial step for the SILAB evolution is to better

identify business requirements.

Table 3: Process evaluation.

Poor

(%)

Fair

(%)

Satisfactory

(%)

Excellent

(%)

Standardization 5 21 42 32

Productivity 11 5 37 47

Transparency 11 5 42 42

5 CONCLUSION

Since companies, research centers and universities

are very close due to innovation demand and

dynamic markets, IS-based solutions has been

developed and deployed in order to support both the

management and the engineering. Especially in

experimentation domain in research laboratories, IS-

supported empirical processes should be developed

to control and manage the experiments lifecycle as

well as their roles, activities and products. At

CEPEL, this is happening through a partnership with

a public university. The focus of this paper was to

discuss an overview of SILAB, an IS that manages

clients and laboratories’ actions during processes of

executing tests and certifying equipment. As shown,

SILAB is responsible for real experiments based on

industry demands and is composed by different

modules that effectively control elements/aspects of

experiments.

The development and deployment processes of

SILAB involved eight stakeholders in three years:

four developers, a project leader, a project

coordinator and two domain experts (from the

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client). Some internal tests were accomplished

during the development phase and professionals

from the research center participated during the

homologation tests. Three main difficulties can be

highlighted: (1) the database migration from the

legacy system to SILAB; (2) the automation of

reports generation; and (3) the definition of the

business rules to implement the Client cycle. On the

other hand, three successful aspects should be

considered: (1) the client was always available and

very close to the development team in order to

clarify the requirements; (2) the agile spirit of

releasing small versions as soon as possible; and (3)

the development team was composed by different

professionals, i.e., a designer, two developers, a

database administrator and an analysts.

As future work, according to survey results

mentioned, a new partnership project related to data

quality is ongoing and it will allow analyzing how

SILAB can be used to improve the research center

business model. In this case, our research group will

use this real scenario to apply data quality

techniques in order to reengineer SILAB and to

better evolve its underlying workflow. The idea is to

evolve SILAB from a system to a platform that

should provide resources to create a software

ecosystem based on the contributions from other

companies related to the energy domain.

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