Research A rticle
Telefacturing Based Distributed Manufacturing
Environment for Optimal Manufacturing Service
by Enhancing the Interoperability in the Hubs
V. K. Manupati,
1
M. Gokula Krishnan,
1
M. L. R. Varela,
2
and José Machado
3
1
School of Mechanical En gineering, Division of Man ufacturing, VIT University, Vellore, Tamil Nadu, India
2
DepartmentofProductionandSystems,SchoolofEngineering,UniversityofMinho,Guimar
˜
aes, Portugal
3
Department of Mechanical Engineering, School of Engineering, Un iversity of Minho, Guimar
˜
aes, Portugal
Correspondence should be addressed to Jos
´
e Machado; jmachado@dem.uminho.pt
Received 16 June 2016; Revised 20 November 2016; Accepted 28 December 2016; Published 7 March 2017
A
cademic Editor: Luis Carlos Rabelo
Copyright © V. K. Manupati et al. is is an open access article distributed under the Creative Commons Attribution License,
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Recent happenings are surrounding the manufacturing sector leading to intense progress towards the development of eective
distributed collaborative manufacturing environments. is evolving collaborative manufacturing not only focuses on digitalisation
of this environment but also necessitates service-dependent manufacturing system that oers an uninterrupted approach to
a number of diverse, complicated, dynamic manufacturing operations management systems at a common work place (hub).
is research presents a novel telefacturing based distributed manufacturing environment for recommending the manufacturing
services based on the user preferences. e rst step in this direction is to deploy the most advanced tools and techniques,
that is, Ontology-based Prot
´
eg
´
e . soware for transforming the huge stored knowledge/information into XML schema of
Ontology Language (OWL) documents and Integration of Process Planning and Scheduling (IPPS) for multijobs in a collaborative
manufacturing system. ereaer, we also investigate the possibilities of allocation of skilled workers to the best feasible operations
sequence. In this context, a mathematical model is formulated for the considered objectives, that is, minimization of makespan
and total training cost of the workers. With an evolutionary algorithm and developed heuristic algorithm, the performance of the
proposed manufacturing system has been improved. Finally, to manifest the capability of the proposed approach, an illustrative
example f rom the real-time manufacturing industry is validated for optimal service recommendation.
1. Introduction
In this era of information technology, manufacturing indus-
tries are accosting challenges due to globalization, high
technology advancement, increased outsourcing, and high
consolidation and at the same time an imminent movement
(from rural to urban areas) of skilled technical labors has
led to a risk (shortage of skilled laborers) to a greater
extent. However, in today’s scenario, a substantial num-
ber of manufacturing units are getting distributed due to
shorter product life cycles, customizations, and rapid advan-
cements in information and communication technology
where the strongest interconnections between geographi-
cally distributed resources (machines, manufacturing lines,
plants, and enterprises) can be possible. is highly ecient
collaborative working environment has led to a stier com-
petition among the globally distributed manufacturing units.
erefore, in order to ensure high competitiveness among
them,industrieshavechangedtheirtrendfromtraditional
manufacturing approaches to swily design and manufacture
products of any quantity yet highly customized [].
In view of attracting the customers, manufacturing unit
worked in a distributed environment by being divided into
small subcompanies having a distinctive fundamental busi-
ness but centralized towards the production of a specic
groupofproductsthatgivesanupperhandtothesmalland
medium scale enterprise (SMEs) to compete in the global
economy. On the other hand, manufacturing units even go to
the extent of sharing their skills, techniques, and knowledge
base to achieve self-accomplishment in the ever changing
Hindawi
Journal of Engineering
Volume 2017, Article ID 9305989, 15 pages
https://doi.org/10.1155/2017/9305989
Journal of Engineering
global market []. erefore, management of manufacturing
functions inside the shop oor , that is, process planning and
scheduling as well as enhancement of workers skill levels, is
of great interest; this has been clearly discussed in the later
sections.
Process planning and scheduling are two important func-
tions in any manufacturing system, where process planning
species which tasks (operations, controls, transports, and
stores) to perform and scheduling refers to the allocation of
resources in the shop over a planning horizon to manufacture
the various tasks of the parts []. Obtaining the optimality by
managing these two functions oen witnesses conict under
traditional approach; that is, the manufacturing functions
were carried out in a sequential manner, in which scheduling
has b een performed aer generation of the process plans.
is process leads to possible loss of real-time schedules
(Bratoukhine et al., ; Wada and Okada, ; Cheng et
al., ). In [] the diculties in traditional manufacturing
approachandtheobstaclestoimprovingtheproductivity
and responsiveness of the manufacturing systems have been
clearly stated.
To overcome the above-mentioned problems in tra-
ditional manufacturing approach in this customer-driven
market, integration methods have been proposed to resolve
thedilemmasinmanufacturingfunctions.In[,],the
fundamental concept of process planning and production
scheduling has been introduced. Till date, numerous strate-
gies and methodologies have been developed for enhancing
the adaptability of the integration approach on manufactur-
ing systems for acquiring better execution of the framework
[]. As of late, much consideration towards agent/multiagent-
based approach has been shown by a number of researches
for integrating the manufacturing functions, especially in dis-
tributed environment. Li and Chaoyang [] made a detailed
literature review on Integration of Process Planning and
Scheduling (IPPS), particularly on agent-based approach and
itsadvantagesoverdistributedmanufacturingsystems.AnN-
person noncooperative game-theoretic approach to generate
theoptimalprocessplansformultiplejobsinanetworked-
based manufacturing system has been presented []. To
develop more eective and ecient solutions of the game,
a hybrid adaptive genetic algorithm has been generated.
e extension of the above work has been carried over in
[, ]. In their work, a hybrid-DNA based evolutionary
algorithm was developed for acquiring feasible process plans
of multiple jobs. At last, their results demonstrated signicant
improvement over other algorithms and better performance
of the system.
Additionally, to compensate the shortage of skilled labors
the implementation of dierent approaches inside the pro-
duction system to enhance its control is highly desired. One
such approach is teleprocessing based manufacturing support
system, called telefacturing. We dene telemanufacturing as
the activity where a rm utilizes services aorded via com-
munication networks and across information superhighways
to perform, in real time, operations and processes necessary
to the design and production of items (Carl Wolf et al.,
). Henceforth, to alleviate the above-mentioned issue of
nonavailability of skilled workers, the current paper presents
a new paradigm in the distributed manufacturing environ-
ment, t hat is, telefacturing which isolates the workforce and
thefactory,wheretheenterpriseisestablishedinsucha
way that it can function in areas which are more suited for
manufacturing processes with lower tax rates and land values,
whilsttheworkerscanperformandresideinareastheywish
such as metropolitan and urban areas. In this kind of pattern,
workers in distant locations can be able to perform their job
remotely by simply controlling robots and remote sensing
and other telecommunication devices [].
However, in such a geographically distributed environ-
ment, the most challenging part is the collaboration and
coordination among enterprises for mutually exchanging the
information []. It has been stated that an Ontology may
be considered as a mode for interoperating all application
soware that can share the information during coordina-
tion by Panetto et al., . Interoperability is dened as
the capability of heterogeneous systems or components to
communicate information and to utilize the data that has
been exchanged. ough the system or components are
heterogeneous, they are interlinked with each other through
a network, as our primary intention is to ascertain that
all the entities like machines, humans, soware agents, and
suppliers can reciprocate information and knowledge without
any signicant loss of data []. Owing to this, the necessity
of interoperability has led to the following prerequisites; all
the data shared by various agents must be systematized in
a common form, and it is to be garnered in an Ontology.
Approach to this Ontology has to be ensured by using
common language, with adaptability to each entity (Daniel
et al., ).
Motivated by these factors, we ha ve explored the possible
issues which may arise in real-ti me (virtually) implemen-
tation of telefacturing approach. In this study, we have
concentrated on two aspects: initially, Integration of Process
Planning and Scheduling in a proposed approach and, later,
predictingtheworkersskilllevelandthenenhancingtheir
skills to perform multiple tasks from a common place (hub)
thereby minimizing the processing time of each worker by
assigning optimal appropriate tasks in a hub. In telefacturing,
as all the enterprises have to communicate with hubs (a
common place for workforce) to synchronize the varied tasks
in a system of enterprises, machines, shop oors, suppliers,
and interoperability issue may arise. All the jobs among the
enterprises a nd the hubs and vice versa in a telefacturing
environment may have diverse control systems, and exchange
of information related to business processes, product data,
and documents to the hubs has become tedious. Hence, to
enhance the interoperability and to solve the communication
among the enterprises and hubs it is necessary to develop a
common language which is light in weight and easily t rans-
ferrable. erefore, we introduced Ontology-based XML
(Extensible Mark-up L anguage) les which can be used as
a common language to transfer the diversied information
without any interruption and mutual exchange of massive
data. In order to support the customer to access such large
data, queries were made possible with the Ontolog y. In the
quest to achieve the above-mentioned requirements, a frame-
work has been developed with telefacturing approach and
Journal of Engineering
with a case the eectiveness of the model is tested. Moreover,
a heuristic has been developed to determine the qualied
worker among trained skilled workers for performing the
multiple tasks at the hub according to the availability of
the job. Consequently, the objectives include minimizing
the processing time of each worker by assigning optimal
appropriate tasks in a hub and henceforth reducing the
workload of each hub.
In Section , we have briey discussed telefacturing
approach and developed a framework model based on it.
In Section , we have used soware Prot
´
eg
´
e . to develop
an Ontology representing knowledge ab out jobs, machine,
process plans, operating time, and so forth, and later XML
les are generated. In Section , we presented a case study.
Section includes experiments with real-time data and
explains the algorithm for the proposed method. In Section ,
discussions about results were specied. In Section , we have
concluded with providing insights about the future work.
2. Collaborative Telefacturing Environment
Telefacturing is a new kind of distributed manufactur-
ing environment where it enables the integrated informa-
tion/knowledge right from product design to manufacturing
with the capability of sharing resources between geograph-
ically distributed enterprises. In general, the enterprises are
locatedinruralareaswherethecheaperlandcostsare
favorable. In the proposed telefacturing approach, factories
couldsetuphubsinthecloserproximityrangetothe
residential areas. is virtual hub will act as an alliance
of enterprises that are willing to share their skills, core
competencies, and resources so as to respond swily to the
market demands. In the near future, possessing or operating
hubsofthesekindscanalsoemergeasapotentialbusiness
idea,asthesehubscanalsoturntobeacommonwork-
placeforanumberoffactories.iscollaborativeservice
support system is capable of carrying out customer requests
through manufacturing information network (application
service layer) through virtual agents. It provides enterprises
with resources such as capabilities and processes that are
highly expensive and too complicated. It makes use of the
expertise of various groups situated at various geographical
areas and integrates distributed processes into the common
manufacturing process.
Additionally, for the workers who do not like to work
alone in the home, the hub is a place where the workers
can socialize with other fellow employees []. According to
the proposed concept of telefacturing, we present a frame-
work model, which is illustrated in Figure . It is developed
by incorporating three-degree networked structure (user/
application/simulation).
In this aforementioned approach, the process initiates
with customer requests whose work task can be taken care of
by network based manufacturing service by means of either
Customer User (CU) or Enterprise User (EU). Customer
User is basically an organization which gets requests for
manufacturing from the customers and to evaluate the tasks
(identifying the related enterprises and interaction with
servers and customer) with the help of their decision system.
However, each customer has their own database and their
own supporting system from which the enterprises can be
chosenaccordingtothetasktobeperformedsoastoprovide
aprotablesolutioninaproductivemanner.Analyzing
manufacturing requests from multiple organizations is also
possible here, whereas the Enterprise User because of its self-
ser vice providing capability (it has the facilities to perform
some of the tasks of customer requests) part of the work can
be taken care of by EU itself. e remaining operations can
bechosen(soastoselectpotentialenterpriseforcarrying
out customer requests) from their available database in the
application service layer. In this manner , CU and EU are
able to achieve diverse and more challenging product i on
tasks that are unaccomplished by a single enterprise (Zhang
et al., ). Aer acquiring required product data and
the enterprise’s information, a suitable approach to dening
the task requirements and its implementation in distributed
environment is carried out.
Here,thejobsdatacanbeexchangedandtheiropera-
tions can be performed through limited/higher bandwidth
Internet connections, allowing the workers the exibility to
operate the machines at the shop oor either being at home
or being at dedicated hubs. Additionally, workers in distant
locations can be able to perform their job remotely by simply
contro lling robots and remote sensing and other telecom-
munication devices. is proposed approach oers copious
advantages such as the dependency on manual workforce,
and the consequent errors and injuries can be uprooted
by minimizing human exposure to various potential health
hazards. Manual laboring errors not only injure people but
can also account for momentous economic loss by damaging
machinery and tools. As mentioned earlier, it can also repress
theoperatingcostsbyusingthemodestlandforoperation.
In addition to that, a teleoperated factory does not have to
comply with vital human requirements for lighting, food,
and other services. Conjointly this approach allows for lower
operating costs. Another noteworthy aid is that telefacturing
factories can accommodate a minimal number of engineers
and technicians sucient enough to rectify certain issues like
replacement of worn-out parts. In fact, to perform tasks with
the above-mentioned virtual environment, it is necessary to
have detailed information of the system congurations and its
setup, and this will be investigated in our future work. In this
work, our main idea is to improve the hubs and enterprises
operations and thereby proper integration of both and also to
imp rove the performance of the system. Telefacturing is also
environment-friendly in the fact that it preserves the required
time and energy for commuting workers from long distance
during rush hours, as it gives them the exibility to work from
less populated areas with customized time schedule [].
3. Ontology Knowledge for
Telefacturing Environment
In a telefacturing environment, the manufacturing tasks are
related to planning, allocation, ordering, machining of parts,
assembling, and so forth. erefore, it is necessary to e-
standardize the resources that can be helpful for sending
and exchanging the information. It can be accomplished by
Journal of Engineering
Customer requests
for manufacturing
a product
Enterprise User
Customer User
Optimization
service
Analysis service
Genetic algorithm
Nondominated
sorting GA
MAS visualisation
service
Network protocols
Knowledge based
system
User service layer Application service layer
Optimization/
simulation service
House
Enterprise
Hub
Bandwidth connection
···
F : e framework of the proposed telefacturing approach.
using Ontology, and it is dened as the means of knowledge
representation. Ontology is able to provide all the deni-
tions of components or systems and their communications
in a distributive environment so as to make a common
understanding for reciprocation of information []. RDF
andOWLlesgeneratedfromanOntologyareWorldWide
Web consortium (WC) standard semantic language for
publishing and sharing of information online (Jinag et al.,
).
In order to achieve the above standardization, in this
diversied distributed manufacturing system, addressing
interoperability is the key. Many authors have decomposed
interoperability into several layers. However, European Inter-
operability Framework (EIF) have categorized interoper-
ability into three layers: technical, semantic, and organi-
zational layers. Technical interoperability deals with issues
related to connecting computer system and services. Such
issues are data mixing, data exchange, security related, and
interlinking s ervices. Meanwhile, semantic interoperability
deals with validating that the exact denition of exchanged
data is understandable by applications other than originally
intended applications. Organizational interoperability deals
with business administration and goals and processes to
amalgamate organizations that are willing to exchange infor-
mation. Open standards like XML and Ethernet will help to
overcome the issues of technical interoperability [].
Oneoftheprimaryneedsofthisenvironmentiscollabo-
rative information management system [], where it can be
able to oer its support to geographically distributed enter-
prises in completing the task collaboratively in many ways.
Figure illustrates database framework for the proposed
telefacturing approach where it consists of two modules:
enterpriseandhubdatabase.Anenterprisedatabaseisusedto
save the product resource information, BOM, process plans,
engineering drawings, supplier related information, and so
forth for maintaining the consistency of enterprise’s data and
Journal of Engineering
Product
resource
Optimal
process
Supplier
information
library
Strategy/
development/
diversications
Budgeting, stock
levels/customer
orders
Knowledge database
of an enterprise
Knowledge
database of a hub
Enterprise
model library
Multiagent
model library
Manufacturing
resource library
Process model
library
XML data
Quality data of
individual
requirements
plans
library
markets/
F : Framework illustrating databases of hub and enterprise.
to reduce data termination. Here, the primary knowledge
for enterprise and task evaluation is kept in hub database
that oers support to the selection of potential enterprises,
valuation of manufacturing capabilities of the enterprises,
quality control serv ice, prots, production status, and so on.
e above-mentioned approach of storing the information in
databases will help to resolve the problem behind exchanging
and integration of diversied information structure in the
telefacturing environment. In the next sections, the proposed
approach implementation over the real case with prototype
example is carried.
4. Case Study of Telefacturing Based
Manufacturing System
iscasestudyhasbeentakenfromamediumscaleindustry
which is located in southern part of India. e region of
this industry has evolved into a potential manufacturing base
that includes several other enterprises. All these enterprises
supplement each other to manufacture a specic range
of products. Due to the prevalence of problems such as
interoperability, high labor costs, and shortage of skilled
laborers, these industries are hardly competitive in the global
manufacturing scenario. In order to overcome all the above
issues, industries are analyzing the possibility of incorporat-
ing collaborative manufacturing techniques. In light of thes e
developments, companies need to nd enterprises with sim-
ilar interests to enhance their manufacturing resources. We
have considered a set of jobs submitted by dierent customers
denoted as n.Eachjobhasanumberofalternativeprocess
plans representing various ways of sequential operations. In
other words, a number of machines may perform dierent
operations for alternative process plans. On the other hand,
in t his proposed manufacturing methodology, alternative
machines are located in dierent geographical areas to p er-
form the required operations on the job. is could be one of
the dicult tasks in the present manufacturing approach con-
taining heterogeneous support systems. Due to the exibility
oftheproposedmethod,integrationofprocessplanningand
scheduling helps us to make an optimal process plan, even
though transportation times between machines are vital for
process plan and scheduling. e objective of this paper is
to provide an approach that can minimize the makespan
of multiple jobs and to identify the qualied worker for
performing tasks in the hub with a motive to minimize the
processing time for each worker, thereby determining the
total training cost for each worker. e notations are clearly
described in the Notations. Subsequently the mathematical
model for the above-mentioned two scenarios is formulated
as follows.
4.1. Phase I: Minimizing the Makespan to Complete
the Multiple J obs of Distributed Enterprises
Mathematical model is as follows:
Minimization of makespan =Max
𝑗𝑜𝑝𝑚
.
()
Subject to Constraints. e rst operation in the
alternative process plan p of job j is indicated as
𝑗1𝑝𝑚
+1−
𝑗𝑝
≥
𝑗1𝑝𝑚
,
∈
[
1,
]
,∈1,
𝑗
,∈
[
1,
]
.
()