integration of process planning and production planning and control in cellular manufacturing

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Integration of process planning and productionplanning and control in cellular manufacturingAmir Hassan Zadeh a , Hamid Afshari b & Reza Ramazani Khorshid-Doust ca Department of Management Science and Information Systems , Spears School of Business,Oklahoma State University , Stillwater , OK , USAb Department of Mechanical and Manufacturing Engineering , School of Engineering,University of Manitoba , Manitoba , Canadac Department of Industrial Engineering and Management Systems , Amirkabir University ofTechnology , Tehran , IranPublished online: 30 Jul 2013.

To cite this article: Amir Hassan Zadeh , Hamid Afshari & Reza Ramazani Khorshid-Doust , Production Planning & Control(2013): Integration of process planning and production planning and control in cellular manufacturing, Production Planning &Control: The Management of Operations, DOI: 10.1080/09537287.2013.767394

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Integration of process planning and production planning and control in cellularmanufacturing

Amir Hassan Zadeha*, Hamid Afsharib and Reza Ramazani Khorshid-Doustc

aDepartment of Management Science and Information Systems, Spears School of Business, Oklahoma State University, Stillwater,OK, USA; bDepartment of Mechanical and Manufacturing Engineering, School of Engineering, University of Manitoba, Manitoba,

Canada; cDepartment of Industrial Engineering and Management Systems, Amirkabir University of Technology, Tehran, Iran

(Received 7 October 2009; final version received 12 January 2013)

Organisations willing to succeed in global competition have to integrate their internal and external processes. Thisespecially includes planning and production control (PPC) processes. Optimised allocation of the production resourcesand quick response to demand changes result in lower cost and improvement of production performance. Practitionersand researchers have been trying to achieve these goals using production planning techniques. Although the resultsare significant, it seems necessary to integrate production operations in order to improve the production performance.The goals, information and decisions taken in production planning and control and process planning are often verydifferent and difficult to integrate in Cellular Manufacturing (CM) environments. Designing an efficient PPC systemand integrating it with process planning in a cellular environment is of the same importance. The following paperproposes first a comprehensive framework of integrated process planning and production planning and control inCM. Then, with respect to this framework and utilising the domain knowledge in the area of CM systems, anintegrated model based on Integrated Definition Modeling Language is developed. The application of the models hasbeen considered as a case study for a production system in electronics and telecommunication sector in a plant inIran. The validity and completeness of the proposed model is tested by a panel of experts in the areas of productionplanning and control in CM environments.

Keywords: production planning and control; process planning; group technology; cellular manufacturing; IDEF0modelling

1. Introduction

Production systems are under intensive pressure fromglobal competition. With product life cycle growingshorter, time needed for marketing and different cus-tomer needs have forced producers to improve efficiencyand productivity of production activities. Without majorinvestments, production systems must be able to adaptquickly in response to demand changes. Cellular Manu-facturing (CM) as a promising production system basedon Group Technology (GT) principles involves theprocessing of a collection of similar parts (part families)on dedicated clusters of machines or manufacturingprocesses (cells) (Ah kioon et al. 2009).

The performance of a production system depends notonly on the quality of the composition of the system incells and departments, but also on the quality of theproduction planning system that is being used to planand control the flow of work (Riezebos and Shambu1998). It also depends on the degree of integration ofproduct design, process planning and productionplanning and control. However, to take full advantage of

the benefits of CM, the compatibility between these sys-tems is of the greatest importance. Therefore, the designof a planning and production control (PPC) system thatmeets all of the requirements of the production systemand also provides a suitable field for sharing someobjectives of process planning and production planningand control is a very important activity.

Some contributions are found in literature, indicatingthe applicability of the well-known approaches of plan-ning and control to CM such as Material RequirementsPlanning, Kanban, and Hierarchical Production Planning.Meanwhile, the integration of production planning andprocess planning in CM is also discussed. Very usefulreviews of existing reference models for designingproduction planning can be found in (Riezebos andShambu 1998; Hernandez et al. 2008). Riezebos andShambu (1998) presented a conceptual hierarchicalframework for production planning and control in CM.This framework consists of planning functions, relationsbetween these functions, planning horizon, period lengthand re-planning frequency applied to these functions,

*Corresponding author. Email: [email protected]

Production Planning & Control, 2013http://dx.doi.org/10.1080/09537287.2013.767394

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and the level of decision-making in the productionsystem at which the function operates. Also, their frame-work contains some information on abstraction levels forcertain planning functions (e.g. demand management).

Ciurana et al. (2008) presented a model integratingthe planning of productive processes and the scheduling ofthese processes in a job-shop type manufacturingprocesses. Hernández et al. (2008) proposed anotherreference model for conceptual modelling of productionplanning processes.

Martínez-Olvera (2008) developed an Integrated Defi-nition Modeling Language (IDEF0) reference model of themanufacturing execution processes in make-to-order(MTO) environments. This MTO-based reference modelshows a blueprint of the interrelationships amongmanufacturing activities, business processes and materials/information flows. The ARIS’ Production Planning andControl Information reference model (Scheer 1989, 1991,1998a,1998b), the SIMA Reference Architecture (1996),and Manufacturing Planning and Execution software inter-faces (MPESI) Feng (2000) are some other initiativesrelated to areas of PPC and manufacturing execution sys-tem (MES).

Even if the integration of product design, processplanning and production planning has been intensivelyinvestigatedwithin various manufacturing environments,the system design of an integrated process planning andproduction planning system in CM environment has notbeen examined thoroughly in the literature. In fact, themajority of the literature has been established for theneeds of the job shop environment, which is differentfrom those of the CM environment. Due to the impor-tance of the cellular manufacturing systems (CMS) intoday’s manufacturing world, and because of the limita-tions of existing reference models, the main motivationfor this research is to develop a reference model for inte-grating process planning and production planningactivities which have a high compatibility with the CMenvironments.

CM creates coordination requirements that are relatedto operational planning. A direct translation from tacticalrequirements planning, based on planned operation leadtimes, to operational detail planning of the productionprocess is problematic. The characteristics of the cellscan vary, for example with respect to the degree ofautonomy, multi-functionality of personnel, presence ofbottlenecks, shared resources, duplicated machines, etc.Therefore, each cell has to be planned and controlledseparately (Production Activity Control (PAC) planningfunction); whereas at the same time, another planningfunction is required for coordinating activities amongcells (Factory Coordination (FC)) (Riezebos and Shambu1998). The operational planning consists of cell control-lers (Production Planning and Control (PAC)) and a FClevel, which coordinates activities of the various cells.

Disaggregation of production routes between cells, anddetermination and selection of an optimal productionroute from process planning resource databases, are someof the decisions made at operational level. In this paper,the production planning framework in CM presented byRiezebos and Shambu (1998) is reviewed and modified.We then describe the development of a comprehensivemodel of process planning and production planning andcontrol, which integrates the process and the productiondomains, and an IDEF0 (Integration DEFinition language0) model is developed. The motive for using the IDEF0as structured system methodology is the fact that processplanning and production planning and control involvemultiple goals, which are sometimes conflicting innature. The conflict arises because these two manufactur-ing planning mechanisms are often distinct in theirobjectives, information and decisions, and because ofthat, it is very difficult to synchronize them together.Consequently, the system approach is applicable in thissituation to indentify the different interactions betweenthese goals and how they are affected by aforementioneddecisions and policies. Although process planning andproduction planning do not follow all of the same rules,their objectives are somewhat complementary in thesense that both should reduce the throughout time sub-stantiality while enhancing production flexibility.

The remainder of the paper is organised as follows.It starts with introducing the IDEF0 modelling methodas a system analysis methodology which is used tomodel the development of the process planning and pro-duction planning and control system. Then, a literaturereview on advantages of integrating process planningand production planning and control in CM is presented.In Section 3, we introduce the case study and then, inSection 4, explain our methodology for this study. In thissection, we present the production planning functionsand propose a comprehensive model for productionplanning and control in CM. Moreover, an IDEF0-baseddiagram is derived for each stage of the integratedprocess planning and production planning system (seeFigures 3–11). In Section 5, the correction and complete-ness of the proposed model is validated and finally,Section 6 presents a general conclusion.

2. Literature review

2.1. The IDEF0 function modelling method

IDEF (Integration DEFinition) family of models is one ofthe most popular modelling approaches in the literaturefor enterprise modelling. It is an integration of computer-aided manufacturing language that consists of a set ofre-engineering techniques developed by the Air Force tofacilitate manufacturing automation (Kappes 1997). Ingeneral, IDEF modelling method is a descriptive toolwhich makes use of modelling and graphical and textual

2 A. Hassan Zadeh et al.

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description of functions, information and data, and makesthat a complex system can be broken down into detailsfor analysis. It represents the business processes, since itis easily understood by users who are not experts in theuse of models (Vergidis et al. 2008).

The IDEF method is divided into a number ofdifferent tools with various capabilities, for example,IDEF0 (for function modelling), IDEF1 (for informationmodelling) and IDEF2 (for dynamics modelling). Thesetools supply a powerful means of analysis and develop-ment of systems and can be applied in a variety of sce-narios, including modelling of manufacturing functions,integration of business processes, and so on. Our studyutilises the IDEF0 method within the IDEF family,which is used for functional or activity modelling of awide variety of automated and non-automated systemsfor existing and non-existing systems (Plaia and Carrie1995). It can help in describing exactly what is happen-ing in a system and in as complete a level of detail asdesired. The result of applying IDEF0 to a system is amodel that consists of a hierarchical series of diagrams,text, and glossary cross-referenced to each other (FIPSPub 183 1993; Perera and Liyanage 2001).

The two key modelling components used in IDEF0are:

(1) Functions (represented on a diagram by boxes).(2) Data and objects that interrelate those functions

(represented by arrows).

IDEF0 describes any process as a series of linkedactivities, each with inputs and outputs. External orinternal factors control each activity, and each activityrequires one or more mechanisms or resources (Fülscherand Powell 1999). Inputs are data or objects that are con-sumed or transformed by an activity. Outputs are data orobjects that are the direct result of an activity. Controls aredata or objects that specify conditions that must exist foran activity to produce correct outputs. Finally, mechanisms(or resources) support the successful completion of anactivity, but are not changed in any way by the activity.Figure 1 illustrates generically how IDEF0 is used todepict activities, inputs, outputs, controls and mechanisms.

This paper was motivated by the potential of IDEF0to conceptualise the development of an integrated processplanning and production planning and control system.Section 4.2. will show the different functions and the

level of detail considered for developing the processplanning and production planning and control model.

2.2. On integrating process planning and productionplanning and control

The purpose of process planning is to provide the rout-ing of a previously designed part while having set asequence of operations and their parameters. It requiresfairly reasonable detailed information about the process.However, the purpose of production planning is toschedule, sequence and launch the production ordersspecified on the routing sheet into the activities in thejob-shop with respect to the firm’s strategies and theactual conditions of the production shop floor. The goals,information and decisions taken in production planningand control and process planning are often different and,as a result of that, it is very challenging to integrate andsynchronize them into one forward-moving harmonicfunction (Martínez-Olvera 2008). Both process planningand production planning focus on minimising costs andtimes within the limits of the constraints, while meetingthe requirements. For process planning, these require-ments refer to meeting the product quality, while produc-tion planning should make sure that the due dates aremet. If process planning imposes major constraints onthe production planning task, these planning processesmay be seen to be conflicting, where ideally they shouldbe co-operating. The conflict is mainly caused by thefact that these separate planning processes do only taketheir own requirements, costs function and constraintsinto account. Both process planning and production plan-ning have complementary goals in order to improvecontinuing company productivity and competitiveness.

Process planners and production planners have verydifferent opinions about optimal manufacturing routes.These optimal routes can be different as minimising theprocessing cost of a given part or product in the processplanner’s viewpoint, and improving the time a particularmachine is occupied to complete a job in the productionplanner’s point of view. Furthermore, depending on thecurrent status of all the determinants involved in the pro-duction system including availability of machines, work-ers, parts, etc., the optimal manufacturing routes changesover time. Nevertheless, though production planning andprocess planning mechanisms do not follow all of thesame rules, their proposes are somewhat complementaryin the sense that both should reduce the throughout timesubstantially while enhancing production flexibility.Computer-aided process planning (CAPP) systems havebeen developed as an interface between design and man-ufacturing to help process planners be able to give opti-mal manufacturing orders at any given time (Ham andLu 1988) and to help production planners use standardand optimised routes for material requirement planning

ACTIVITYInputs

Controls

Outputs

Mechanisms (Resources)

Figure 1. IDEF0 building block.

Production Planning & Control 3

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(MRP) (Ciurana et al. 2008). Technological variablessuch as tolerances, specifications and materials are majorinput of these systems which are used to calculate theoptimal and standard routes. The routings specify manu-facturing operations and sequences containing detailsabout work centres, standards, tooling, fixtures, speeds,dimensions, etc. (Mujber et al. 2005). This routingbecomes a major input to MRP system to determineoperations for the purpose of production activity control(PAC) and identify required resources for the purpose ofcapacity requirements planning (CRP). Given the factthat the production planning variables (resources avail-ability, etc.) are not inputted into the CAPP system, theoptimised route recommended by this system may notguarantee the best sequence to manufacture the parts at adesired time, as it could lead to the subsequent bottle-necks resulting from overloading or under-using of somemachines. However, the severity of these bottlenecks canbe resolved through generating alternative routes pro-vided by the CAPP system, rescheduling them duringthe following working shifts (Grabowik et al. 2005).

Especially in CM environments, while the researchon the basic issue of cell formation continues (Viswana-than 1996; Wang and Roze 1997), the trend is towardsdesigning cells which incorporate wide range of produc-tion data as well as imbedding required level of flexibil-ity into the cell system design (Dahel and Smith 1993;Askin et al. 1997). Integration of cell formation withother functions such as production planning (Schalleret al. 1998), process planning (Wang and Roze 1997)and capacity planning (Ramabhatta and Nagi 1998;Wilhelm et al. 1998) was reported in the literature.Integration issues in CM are mainly concerned with theefficient integration of three major concerns: (1)planning-oriented predictive cellular layout design; (2)an unexpected order-adapted CM through the integrationbetween manufacturing decision processes and cellularlayout; and (3) a contingency-driving shop floor adapta-tion for supporting continuous improvement. The possi-bility of sudden large changes in demand rate andprocess route is greatly reduced by both the detailedanalysis of decision processes and the reconfiguration ofexisting facilities through workers’ high skills. Toincrease the ability of reaction to shop floor contingen-cies, real-time information on the conditions of the shopfloor will be analysed to support continuous improve-ments for sustaining superior performances in the eventof unexpected changes. The continuous improvementssupport the user with five modules: real-time statusmonitoring; real data analysis and forecasts renewal;diagnosis through intelligent decision support system;simulation optimisation; and results evaluation and per-formance measurement (Song and Choi 2001).

Many authors proposed models for integratingproduction planning and process planning. Larsen and

Clausen (1992) suggest that, in general, process planningincludes two major phases, the first to be classified astime-independent and the second as time-dependent(Giebels 2000):

• Analysis phase. Technical analysis of candidatesolutions

• Selection phase.

In the literature, the terms ‘macro process planning’and ‘micro process planning’ are often used. The pre-fixes ‘macro’ and ‘micro’ point out the level of detail inthe process plans. Macro process planning is associatedwith the rough technological planning of process selec-tion and design activities on an aggregate level, whilemicro process planning is associated with the detailedtechnological planning of process activities resulting inthe manufacturing functions (Giebels 2000). Srinivasanet al. (1999) suggest that macro process planning refersto the determination of a feature sequence through theanalysis of geometric and process interaction. Micro pro-cess planning refers to intra-feature planning, i.e. theoptimisation at the feature level (Sheng et al. 1996). Cayand Chassapis (1997) express macro process planning asthe manufacturability layer while the detailed processplans are generated through micro process planning.

Due to importance of process planning levels in CM,in our study, micro process planning and macro processplanning modules are added to the framework (seeFigure 2). The motivation for this research to add processplanning modules emerges out of the fact that while exist-ing frameworks have considered various sub-functions inthe design of CMS, the aspect of integration of productionplanning with process planning in a comprehensiveconceptual model has not been wholly considered.

3. Printed circuit board (PCB’s) industry

The case company is a specialty PCB manufacturerproducing a large variety of high-quality PCBs forelectronics and telecommunication factories for the past20 years. The company has the ability to build all catego-ries of PCBs. The existing layout of the manufacturingsystem consists of manufacturing cells, each beingdedicated to the processing of an individual productfamily. They utilise the formation of part families bystandardising similar products for different customers atthe product design stage in order to maintain the currentsystem. The formation of part families is based uponsimilar processing requirements and the grouping ofmachines into manufacturing cells to produce them. Thecells consist of various types of machines and operators.Variables, such as the multi-functionality of employees,the sharing of key machines between cells, and the exis-tence of bottlenecks, can make it difficult to maintain agood balance between inter-cell and intra-cell machine


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utilisation and operator utilisation. Though the companyuses commercial planning systems (e.g. ERP, MRP) for

tactical and operational levels and manufacturingexecution systems (MSE) for data acquisition and control

5. Case study

Demand Management:

Order Information

MasterProduction Scheduling

Material Requirements

Planning

Purchasing Subcontracting

CapacityRequirement

Planning

H: year F: month P: month

H: 3 month F: week P: week

H: 2 month F: week P: week

H: weekF: day P: day

H: 2 days F: day P: shift/hour

Legend H: Horizon F: Frequency P: Period length

Demand Management:

Product Families

Aggregate Production PlanningLot Size and Safety

StockDetermination

Rough Cut CapacityPlanning

Remainder Shop

Scheduling

Lead time>2 month

Intra-cell Scheduler

Intra-cell Dispatcher

Intra-cell MonitorIntra-cell

Schedule

Coordination GuidelinesFor each PAC System

Information FromPAC Monitors

Request

Inter-cell Scheduler

Schedule guidelines

Detailed Schedule Request

Control Activity in Intra-cell Module of Cells

Inter-cellDispatcher

Inter-cell Monitor

Performance Measures

Process Data

Information To Factory

Coordination

Status

Cel

l Lev

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Movers Producers

Instructions

Equ

ipm

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evel

Sub-Movers Sub-Producers

Instructions Information Instructions Information

Execution Layer (Devices etc.)

Control Activity in Inter-cell Module of Cells

MacroProcessPlanning

MicroProcess

Planning

Figure 2. A comprehensive model of integrated process planning and production planning and control in cellular manufacturing.


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on the shop floor, the integration of them is still achallenge.

One major obstacle that the company suffers from isthe lack of control and flexibility in the production systemto cope with shared resources (key machines, multifunc-tional operators, etc.) between cells, dispatching andreleasing work orders to these resources and from them toregular manufacturing cells; this results in backorders, latepenalties and fees, and customer dissatisfaction. Anotherproblem the manager mentions is disagreement betweenprocess planner and production planner associated withoptimal manufacturing routes. The process planner andproduction planner have very different opinions regardingoptimal routes. Therefore, the integration of productionplanning functions with process planning functions shouldbe investigated in a collaborative manner.

The interviews with the company’s personnel and thedomain definition provide the modelling scope of theproduct, information and decision flows. The followingsections represent the conceptual design of the recom-mended system for integrating process planning andproduction planning, which is derived from combiningand integrating both academia and industry initiatives. Itis important to highlight the fact that in electronics andtelecommunication industry in Iran, most of the partsand raw materials are imported, which increases the levelof uncertainty. This circumstance is not compatible withKanban system; hence, the classical PAC model shouldbe used.

4. Methodology

In order to deal with this research objective, we usedfollowing four-stage approach similar to Martínez-Olvera(2008) to build the model:

Stage 1: The first phase consists in obtaining anadequate understanding of the processes and activities inorder to define the system scope and boundaries. It isoriented to establish and support the analysis of theprocesses from the existing documents in the enterprise.

Stage 2: A conceptual design approach is followedby combining and integrating both academia andindustry initiatives containing the essential elements ofthe production planning systems (see Figure 2). Thebasic functions of the framework and the logical interac-tions between them can be established via the analysis ofexisting literature.

Stage 3: An IDEF0-based diagram is derived for eachlevel of the integrated planning (see Figures 3–11 later).These activity-driven models can be used to develop asystem where the production and the process plan can becreated concurrently in an collaborative engineeringwork. We focused on integrating process planning andproduction planning and activities related to productioncontrol adapted to shop floor characteristics which have a

high compatibility with the CM environments. The mainreason for using an IDEF0 diagram is that it is designedto model decisions, actions and activities of a system,and its main strength is its simplicity, as it uses only onenotational construct called the ICOM, input-control-out-put-mechanism.

Stage 4: In order to provide a solid base of validation, apanel of experts was formed from a pool of experiencedproduction supervisors, engineers and managers in theareas of production planning and control to evaluate andsupport model development. A survey questionnaire wasdesigned and used as the primary data collection method toidentify possible strengths and weaknesses of the model.

4.1. A comprehensive framework of integrated processplanning and production planning and control in CM

Various production planning frameworks in CM basedon ideas of material requirements planning, just in timeand optimised production technology, have been devel-oped by system analysts. Riezebos and Shambu (1998)developed a conceptual model for production planningand control in CM consisting of planning functions, rela-tions between these functions, planning horizon, periodlength and re-planning frequency applied to these func-tions, and the level of decision making in the productionsystem at which the function operates.

According to the application of Banerjee (1997) meth-odology in production planning and control for CMS, acomprehensive framework for designing a productionplanning and control system in a specific productionsystem should specify both

• the required planning functions and• the direction and contents of the relationsbetween these functions.

In the framework presented by Riezebos and Shambu(1998), the following steps can be performed to modifythe framework:

(1) Capacity is considered as a black box. While itseems to be necessary that in order to checkcapacity in various level of production planning,known planning functions related to capacity (e.g.Rough Cut Capacity Planning [RCCP] andCapacity Requirements Planning [CRP]) have tobe used and added to framework.

(2) Decisions in each level are taken for satisfyingobjectives of same level and taking account-imposed situation from upper levels and feedbacks of lower levels. In each level, if imposedsituation from upper levels cannot be satisfied, itis necessary that plans of upper level should berevised by feedback loop until feasible plans inlower levels can be achieved. Because of that, itis necessary to add feedback loops to framework.


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(3) Cell coordination is not explained in detail. Thus,the coordination procedure is vague. To overcomethis weakness, models presented by Bauer et al.(1994) are used to clarify functions of cellcoordination.

(4) Nevertheless, variant modules are addressed inthis framework; process planning functions are notillustrated. To integrate process planning in vari-ous level of production planning, known macroprocess planning and micro process planning haveto be used and added to framework.

Figure 2 shows this comprehensive framework of produc-tion planning and control in CM. Data flow has beenadapted to cope with the characteristics of the case study.As mentioned earlier, electronics and telecommunicationsector in Iran is exposed to high levels of uncertainty insupplying raw material. To deal with this uncertainty, thePAC model presented by Shahid (2006) and Bauer et al.(1994) is used to clarify functions of cell coordinationand PAC, respectively, by FC and Production Planningand Control (PAC).

The hierarchical PPC framework includes managerialdecisions ranging from aggregate production planning

level to factory coordination and production control inmanufacturing cells, having into account the resourcesaggregation and abstraction of information, productionorders, and frequency of (re)planning along with variousstages feedback. The framework initiates with variousplanning modules at the highest level including aggregateproduction planning, demand management, rough-cutcapacity planning and macro process planning. Thesemodules can be performed at an aggregate (product fam-ily) level. The aggregate planning typically deals with thedevelopment, analysis and maintenance of plans for totalsales, total production, targeted inventory and targetedcustomer backlog for families of products over times.The initial purchase decisions of very long leadtime itemscan be made at this planning level (Riezebos et al. 1998).This level performs a capacity check by rough-cut capac-ity planning function, so the available capacity of thevarious clusters (a rough measure) is compared with thecapacity required by the aggregate plan and a macroprocess planning function that concerns the roughtechnological planning of production activities on anaggregate level. Products’ selection and families’formation, conceptual cells instantiation, process require-ments specification, process flows specification, material

A0

Planning Integrated & Control System For Cellular Manufacturing

Design ChangeRequest

Knowledge

Databases

Capacity

Times

Draw Part

Market Demand

Machines& Fixtures

Personels

Customer Requirement

Purchase Requirements

OutsourceRequirements

Products

Cost Report

:EDON :.ONA0 TITLE: gnirutcafunaM ralulleC roF metsyS lortnoC & detargetnI gninnalP

Total Cost

PlanningPolicies

Decision Support

Simulation Software

Approaches toProduct Selection

& Families Formation,Cell Formation, Systems

Development& Balance

Computation System

Cells Formations & Layout

Tools

Figure 3. Top level of the IDEF model.


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flow requirements definition and support systems require-ments definition are done in the macro process planninglevel. This plan is updated monthly. The next planninglevel is master production scheduling. This module usescustomer order information and performs at individualproduct level, not aggregate level. At this level of produc-tion planning, using capacity requirement planning func-tion, the amount of available capacity of the variousresources required by the master production schedule ischecked. This plan needs to be updated on a weeklybasis. This planning level initiates material requirementplan at the next level which uses information on theplanned production of the end items, bill of materials,batch sizes and safety stocks to “time phase” the require-ments for the production units, having into account thestandard cycle times. Also, MRP presents information onthe expected amount of raw material needed to the sup-pliers. The intra-cell coordinators schedule on the basis ofthis information. They use information of the MRP onthe planned start times of the various components todetermine the actual priority of the various released workorders and the micro process planning function to deter-mine workstation instantiations, raw material require-ments, options for operation and machines, sequence

operations in machines, as well as tools and conditionsrequirements (Riezebos and Shambu 1998).

The coordination of work between manufacturingresources or cells is an essential requirement of CM sys-tems. The main objective of this Intra-cell coordinator isto establish an arrangement of the machines and otherresources in order to minimise the movement of peopleand the handling of materials, thus ensuring good levelsof performance. Additional forms of cell productioncontrol including strategies for solving several dimen-sions of the scheduling problem are defined. This level ofplanning is daily updated (Carmo-Silva and Alves 2006).

Decisions of FC level of planning and control areconcerned with:

(1) Disaggregating of production routes between cellsalong with determination and selection of anoptimal production route from process planningresource databases result in consideration of thefollowing:

• Current operating situation on the factory andthe shop floor of cells optimises the flow ofmaterial and the use of the resources involved inmanufacturing and assembly,

A1

Develop Process Plan

A2

Develop Production Plan

A3

Production Control

Draw Part

ProcessChange Request

Operations

Times

Total costdatabases

knowledge

Alternative Routings

MPS

MPS,MRP Change Request

Market Demand

Performance(feedback)

Mfg. Orders


OutsourceRequirements

Tools

Machines

Simulation software

Capacity BOM

Design ChangeRequest

Cost Report

PriorityRules Cells

Products

Instructions

TITLE: :EDON :.ONA0 MC roF lortnoC & detargetnI gninnalP

Rout sheet

Time

Cost

Figure 4. First level of the IDEF model.


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• Various management goals like reducing thework in process and the severity of bottlenecks,minimising shop floor throughput in cellsand lead-times and improving delivery dateadherence.

(2) Identifying orders appropriate sequences betweenthe cells and planned throughput times per cell.

(3) Control Intra-cell good flows.(4) Determination of batches that contain families

of parts and consideration of the cell as oneplanning unit.

(5) Control the available capacity of cells, schedulemanufacturing orders and shared resourcesbetween cells, dispatch and release work orders tocells.

(6) Monitor work orders released to cells and sharedresources and send updated information to upperdecision levels.

(7) Establish the number of workstations andmachines per workstation precisely, which havebeen roughly estimated at the conceptual design

level, as well as other production resources thatmay be required to operate workstations.

The undermost level contains control activity ininter-cell. This module can be performed at an opera-tional order level: product batches/lots. The cells dailyobtain orders from the cell coordinator. The availablecapacity in these cells is controlled by the coordinatorfunction, and reallocating work to one of the other cellsor an (external) sub-contractor is used to solve short-termloading problems. Work order release to the cells isperformed by the cell coordinator function. The cellsobtain the information themselves through the FCsystem. Cells’ performances are controlled from the PACfunction. PAC is the process by which manufacturingresources are coordinated, scheduled and controlled inreal-time. PAC is responsible for the management of thecells’ shop floor production task. Bauer et al. assert thatproduction control performs three essential functions:

(1) Continuous determination of timing for controlla-ble events, thus creating a detailed productionschedule (Dynamic Scheduling)

TITLE:NODE: NO.:A1 Develop Process Plan

A11

Develop Macro Process Plan

A12

Develop Micro Process Plan

Draw Part

Production Orders

1th Level Family Formation

Product Model& Families

Mfg. Features

DatabasesKnowledge

Product Selections& Families

Conceptual Design

Integrated ProcessSpecifications

Product Selections& Families

Conceptual Design

Approaches toProduct Selection

& Families Formation,Cell Formation

& Systems Development Time & CostRef. data

Support SystemsRequirements

Production Systems Library

Process Model

Cells SizeWorkstations

Operator’s Allocation

Route Sheet

Cost

Time

Tools

Balance Methods

Machines& Fixtures

Support Systems

Figure 5. Process planning level of the IDEF model.


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(2) Real-time collection and evaluation of productiondata detailing the state of the system with thegoal of modifying the schedule and improvingthe dispatching function (Monitoring).

(3) Execution of the current schedule relative to thecurrent state of the production system (Dispatching).

The framework also shows that the PAC levelplanning is updated hourly or during each shift. Also,the schedule plan of the PAC level is being updated farmore frequently than the remainder of the shop’sschedule. 5. Case study

4.2. Detailed design of integrated process planning andproduction planning and control system

In this section, an IDEF0 model based on comprehensiveframework of integrated planning and control depicted inFigure 2 is developed. Based on the IDEF0 methodology

and comprehensive framework introduced in previoussection, the top-level activity is planning integrated andcontrol system for CM (A0), as shown in Figure 3. Infact, it can be presented in the various sequential stepsas it is required to have data associated with the cells,the machines and the tools such as distances betweencells, machines, specifications, market demand, etc.Figure 4 displays the first stage of the decomposedmodel, consisting of three actions or activities: (A1)develop process plan, (A2) develop production plan, and(A3) develop production control. Each of these actionsrequires the development of a set of sub-actions, whichare described in more detail in the following sections.

4.2.1. Process plan

The A1 diagram shown in Figure 5 is the top-level con-text diagram, on which the subject of the process plan isrepresented by a double box with its bounding arrows.

Figure 6. Macro process planning level of the IDEF model.


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This activity is related to the production activity throughthe cost, the time and the routing. Figure 5 shows thetwo main activities that are needed to develop a processplan which are: develop macro process plan (A11) anddevelop micro process plan (A12). The inputs to thisfunction are draw part, product models and families,production orders, manufacturing features, and first levelof family formation. The outputs are the conceptualdesign, the time, the cost and the routing. The constraintsare the availability of resources, like machines capacity.In turn, each of the main activities A11 and A12 isdecomposed into sub-activities which are brieflydescribed in the next two paragraphs.

The micro process planning activity (A11) relates todeveloping a specification for the production andsupporting processes required to manufacture the targetpart mix. This activity may be performed jointly withactivity of micro process plan (A12), in specifying themanufacturing processes. This activity, however, concen-trates on identifying processes common to multiple partsin the mix or to other parts manufactured in the samefacility. In addition, this activity specifies the necessary

support operations for the production system, productselection and family formation, conceptual cells instantia-tion, materials management, tooling preparation andmanagement, materials flow, equipment maintenance,workspace requirements, etc. This activity is broken downinto six sub-activities. Figure 6 displays sub-activitiesA111–A116 and the data flow. Products selection andfamilies formation (A111) is a refining process, on theway production of goods will be organised. It can bethought of as a detailed product family formation processthat actually leads to the manufacturing cells to adopt andimplement. The objective is selecting products that aregoing to be manufactured, in the same manufacturingcells. This activity is based on recommended conceptualcells and requires a detailed analysis of processingrequirements based on actual production orders of specificproducts and product components. Processing require-ments are indicated through operational plans, with a clearidentification of manufacturing operations’ precedence.Grouping products into families following similarsequencing plans is an extremely critical activity in orderto match the conceptual configurations recommended.

Figure 7. Micro process planning level of the IDEF model.


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The conceptual design phase (A112) postulates concep-tual cells configurations. The main purpose of this activityis to instantiate each of selected conceptual cells on thebasis of resource combination and workstation configura-tions. It depends on processing requirements, operationalneeds and resource availability. Therefore, the quantity,the quality and the type of each specific manufacturingresource such as machines and auxiliary resources includ-ing operators (multifunctional), tools, available in eachworkstation may result in various forms of cell instantia-tion. The output from this conceptual design phase is anumber of cells whose configuration fits the conceptualcell configurations proposed. Also, having into consider-ation operational precedence constraints, operationsequencing plans for each product in a product family arespecified. By specifying process requirements (A113), theprocesses required to manufacturing the target part mixwhich is common to multiple parts in the mix and thosewhich are unique to particular parts are identified. Distin-guishing those processes which may already be availablein the target facility is done in this level. Also, developingrequirements for major equipment is performed in thisactivity. Specifying process flows (A114) relates to devel-oping a detailed process flow diagram for the target part

mix which identifies flows common to multiple parts andestimates volumes of those flows. In this level, uniqueflows for particular parts, including departures from andreturns to the mainstream, and estimate flow volumes areidentified. The process flow diagram is based on the rout-ing of parts and sequencing of operations specified for theindividual parts and explicitly outlines how materials aremoved within manufacturing and assembly cells, havinginto account available resources, time, cost and othermanufacturing constraints. The process flow diagrams(A115) identify the requirements and specifications of thematerials handling, use, storage, buffering, warehousing,transportation, packaging and other logistics support inthe production system. The requirements for material han-dling, buffering and transport equipment are included aswell. Using activity A116, required support systems areclearly defined. It includes the requirements for part and/or product packaging and shipping workstations withinmanufacturing and assembly cells are identified. Forinstance, packaging workstation may take into accountspecifications relative to assembly kits and other specifictransporters. Therefore, in this planning stage, the require-ments for logistics supporting systems, such as materials,parts and products storage, inventory systems, parts

TITLE: :EDON :.ONA2 Production Planning

A21

Demand Management

A24

Develop Master Production Schedule

A22

Develop Aggregate Plan

A23

Develop Rough Cut Capacity Plan

A25

Develop Materal Requirement Plan

A26

Develop Capacity Requirement Plan

MarketDemand

ProductFamiliars

Demand Forcasts

Customer Orders

Capacity Requirements

Revisions

Machine Needs

MRP Plan: Mfg. OrdersPer Week

Outsource Requirements


RevisionsRevisions

AP Plan:Product Familiars

Production amountPer month

InventoryLevels

BOM

Competitive Pricing

MPS Plan: Production amount Per week

DecisionSupport

ComputationSystems

PlanningPolicies

Feasible AP Plan

Route Sheet

MPS Change Request from

Factory Coordination

MRP Change Request from


Times

CostWorkforce, Overtime

,Outsourcing volume

Capacity

Purchase RequirementsWith Long lead Time

Human Resource Needs

Spare PartsDemand

ForecastingTechniques

Figure 8. Production planning level of the IDEF model.


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delivery zones, tool and kit workstations, etc, are speci-fied. Also, specification of scrap, recycle, rework, disposeand materials recovery systems can be included (SIMA1996).

The decomposition of activity A12 is shown inFigure 7, which clarifies the details of developing microprocess plan. We use IDEF0 model developed by Ciuranaet al. (2008) to expand micro process planning sub-activ-ity which has a high compatibility with the CM environ-ments. It initiates with activity A121 ‘workstationinstantiation’ specifying a precise number of workstationsand machines, operators and tools required in each work-station. In this stage, a detailed knowledge of the quan-tity, type and processing capabilities of available mainand auxiliary resources such as machines, tools and oper-ators should be established. The number of operators andthe level of replicated auxiliary equipment, together withtheir dynamic utilisation within cells may substantiallyaffect not only the cell capacity and production flexibility,but also the way in which cells can be operated. Thus,the availability of auxiliary resources and operators

remarkably restricts the high performance levels that canbe obtained (Carmo-Silva and Alves 2006). By activityA122, the dimensions and the shape of the parts are set.Activity A123 determines options to operation andmachines. Generating a sequence of operations executedon the same machine is the task of activity A124. At thenext stage, activity A125, the tools and conditions areselected and their characteristics are established. Finally,activity A126, documentation, is where all the informa-tion in the micro process plan is organised.

4.2.2. Production plan

For the case of A2 i.e. the production planning activity, itis composed by six key sub-activities, as shown inFigure 8 which clarifies the details of the productionplanning activity. By activity A21, it is ensured that thecompany’s business needs are being appropriately metand that resource is not being applied unnecessarily.Activity A22 is implemented to develop an aggregateplan to support the business plan of the company. This

A31

Intra-Cell Control

A32

Inter-Cell Control

TITLE: :EDON :.ONA03 Production Control

MRP Plan:Mfg. OrdersPer Week Purchased Materials

Delivery Schedule

Detail Schedule: Production Batches/Lots

Per Shift/Hour

Route Sheet TimeCost

CostReport Process Change

Request

Shared ResourceSchedule

MPS

Outsourced ComponentsDelivery Schedule

Intra CellSchedule:

Production Batches/LotsPer Day

MRP,MPSChange Schedule

Cells Production Report to Upper Levels

Specifications

Personnel Performance Report

Intra Cell Schedule Change Request to


Machine StatusReport

Process ChangeRequest to


DecisionSupport Production Report

To Factory Coordination

SimulationSoftware

Production BatchesRelease

ResourcesRelease

Priority Rules

Cells Shape & Layout

DatabasesTimes

Costs

Batches/Lots Dispatch List

Capacity

Figure 9. Production control level of the IDEF model.


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tactical plan usually includes the development, analysisand maintenance of plans for total sales, total production,targeted inventory and targeted customer backlog forfamilies of products and over times volume andoutsourcing volume. Also, as mentioned earlier, due tothe existence of high levels of uncertainty in supplyingraw material, this planning level initiates the purchase ofcommon items with very long lead times. This plan ismonthly updated. Through activity A23, Rough-CutCapacity Planning, the aggregate production plan isconverted into requirements for key resources, oftenincluding labour, machinery, warehouse space, andsupplier capabilities. Comparison to available or demon-strated capacity is usually done for each key resource.This comparison makes the aggregate production plan fea-sible. At the next stage, activity A24, Master ProductionScheduling (MPS) is established based on the aggregateplan. MPS is a line on the master schedule grid thatreflects the anticipated build schedule for those itemsassigned to the master scheduler. The master schedulermaintains this schedule, and in turn, it becomes a set ofplanning numbers that drives material requirements plan-ning. It represents what the company plans to produce,expressed in specific configurations, quantities and dates.This activity uses the updated status of the customer’s

order and resources availability involved in the transfor-mation process to determine what, how and how muchare produced. This schedule is updated weekly. By activ-ity A25, MRP is built to determine which sub-assemblies,components and raw materials are needed to produce orpurchase, how much and when they are needed. MRP isa set of techniques that uses bill of material data, inven-tory data and the master production schedule to calculaterequirements for materials. It uses information on theplanned production of the end items (including, for exam-ple, spare parts) and the preferred lot sizes and safetystocks to time phase of the requirements for the variousclusters and production units, using the expected (stan-dard) throughput times. It makes recommendations torelease replenishment orders for material. Further,because it is time-phased, it makes recommendations toreschedule open orders when due dates and need datesare not in phase. Time-phased MRP begins with the itemslisted on the MPS, and determines: (1) the quantity of allcomponents and materials required to fabricate thoseitems; and (2) the date that the components and materialare required. Time-phased MRP is accomplished byexploding the bill of material, adjusting for inventoryquantities on hand or on order, and offsetting the netrequirements by the appropriate lead times. This plan is

TITLE: :EDON :.ONIntra Cell Control

A311

Develop Process Squence & Schedule

A312

Dispach Production

Batches/Lots

A313

Monitor Cells & Share Machines

& Production Batches/Lots

A314

Control Factory Data & Feedback

MRP Plan:Mfg. OrdersPer Week

Time Cost Alternative Routings

Intra Cell Schedule: Production Batches/Lots

Per Days

Route Sheet

Purchased Materials Delivery Schedule

Outsource Component Delivery Schedule

Production Route

Operation Sequence

ProductionOrders

Share ResourceSchedule

CellSchedule

MaterialsAssignment

To cell

ReleasedBatches/Lots

to cells

CostReport

ProductInventory

Share MachinesStatus

CellsStatus

Cells Production Report to Upper Levels



Share Machines StatusReport

OperationsInstructionsMaterial transfer

Request to cells

WIP Inventories transferRequest to cells

MPSCapacity

DecisionSupport

Databases Times Total Cost

Production Batchs/Lots Status: Quality & Location &Time

SimulationSoftware

PriorityRules

Cells

MPS,MRP Change Request

Share ResourceSchedule

Specifications

Figure 10. Intra-cell control level of the IDEF model.


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updated weekly. Finally, using activity A26, CRP, levelsof capacity are established, measured and adjusted. In thisstage, the amount of labour and machine resourcesrequired to accomplish the tasks of production aredetermined. Open shop orders and planned orders in theMRP system are input to CRP, which through the use ofparts routings and time standards translates these ordersinto hours of work by work centre by time period. Eventhough rough-cut capacity planning may indicate that suf-ficient capacity exists to execute the MPS, CRP mayshow that capacity is insufficient during specific timeperiods.

4.2.3. Production control

Production control (A3) is composed by two mainactivities, intra-cell control (A31) and inter-cell control(A32). Each of these two activities (Figure 9) requiresthe development of a set of sub-activities, which aredescribed in more detail below.

Intra-cell control (A31) is a level of planning thatcoordinates materials and information flows among cells(FC level). The main purpose of this activity is to mini-mise the movement of people and materials, thus realis-ing certain levels of performance and quality. It can beachieved through establishing a proper arrangement of

the machines and other resources. Even though concep-tual cells instantiation highly restricts the cell arrange-ments that can be established, intracellular-detailedorganisation and control structure in each manufacturingcell are still needed to be clearly defined. This involveslocation of workstations, machines and auxiliaryresources in each workstation, and also several possiblelayout configurations. Moreover, flow of people andwork within a cell and cell’s operating modes must bestudied and set for implementation. A systematic andintegrated approach for the material handling and storagesystem must be developed in order to treat the intracellu-lar coordination problem within organisation. Thisrequires information about quantity and type of availableresources (machines, operators and auxiliary tools), spaceavailability, quantity, shape, size and weight of produc-tion unit loads handled via equipment, frequency of han-dling, and subsequently costs of handling per each unitproduced. Input and output storage space of both manu-facturing cells and of workstations and also, ergonomicand safety considerations must be clearly defined at thisstage. A31 is composed of four sub-activities, as shownin Figure 10, which are described briefly in the next par-agraph.

By activity A311, operation sequence and schedule isidentified based on the manufacturing orders from MRP

TITLE: :EDON :.ONInter Cell Control

A321

Develop Operation

Squence & Detail Schedule

A322

Dispach Production

Batches/Lots

A323

Monitor Man & Machines & Production

Batches/Lots

A324

Control Cell-Floor Data & Feedback

Intra Cell Schedule:Production Batches/Lots

Per Days

Time Cost Alternative Routings

Route Sheet

Purchased Materials Delivery Schedule

Outsource Component Delivery Schedule

Production Route

Operation Sequence

ProductionOrders

ResourceSchedule

PersonnelAssignment

MaterialsAssignment

ReleasedBatches/Lots

CostReport

PartInventory

MachineStatus

PersonnelPerformance

Production Report to Factory Coordination


To Factory Coordination


Machine StatusReport

OperationsInstructions

WIP Inventories transferRequest to workstaions

MPSCapacity

DecisionSupport

Databases Times Total Cost

Production Batch/Lot Status: Quality & Location &Time

SimulationSoftware

PriorityRules

Cells

Intra Cell Schedule Change Request

Material transfer Request to workstations

Detail Schedule: Production Batches/Lots

Per Shift/Hour

Batches/Lots Dispatch List(FC) Specifications

Figure 11. Inter-cell control level of the IDEF model.


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plan and the MPS. Production operations are defined,sequenced and scheduled locally on the levels of cells,and shared resources in order to reduce the work inprocess and the severity of bottlenecks. Also, otherobjectives, such as minimising shop floor throughput incells and lead-times, improving delivery date adherence,minimising set-up time, minimising idle time, minimis-ing queue time, are optimised. An optimal alternativeproduction route is identified and selected from processplanning resource databases that take into account thecurrent operating situation of the shop floor of cells is aspecific activity that must perform in this level. ActivityA311 is based on the characteristics of the cell’sformation and is related to the process. Activity A312determines which production batch/lot in the queue isbest processed next. The objective is to minimise thelead time and lateness and to reduce the severity ofbottlenecks in cells and shared resources between cells.Using activity A313, cells, shared resources, productionbatches/lots and personnel are monitored in order to pro-vide the information on where any production batch/lotis at all times and its disposition. Also, it provides theproduct genealogical information such as who workedon it, current production information, component materi-als by supplier, lot number, serial number, any rework,mean lot number, serial number, measured data, or otherexceptions related to the product. At the same time, itprovides the status information on specified resources,such as tools, devices, machines, and stock materialsat all times. Finally, activity A314 provides hardware/software interface links to obtain mission-critical datapertinent to production activities. The data from thefactory for multiple purposes such as product throughput,quality, delivery and equipment maintenance arecollected and analysed. Each of these activities requiresthe development of a set of sub-activities. The SIMAmodel (1996) is used to extend the sub-activities. It isimportant to highlight the fact that the SIMA architecture(1996) is too generic and therefore, the process ofcustomisation is required to adapt it to the FC level.

Inter-cell control (A32) is a level of planning that con-trols materials and information flows in shop floor (PAClevel). This is the final step in the detailed design of CMSand is the activity which ultimately guarantees that theintercellular organisation and coordination concept can beimplemented. In addition, at this stage, production relatedwith each individual product order must be synchronisedthroughout the several production stages, at each cell orresource of the CM system. This design stage is verychallenging where complex products with numerous com-ponents along with parallel and series manufacturing andassembly operations are involved. Production in CMSgenerally assumes the existence of connected cells andinterlinked cells, with the output of one cell providing theinput to one or more subsequent cells. The PAC model

and the SIMA model are excellent vehicles for buildingeach stage of PAC.

5. Completeness of the model

The first element necessary to consider the proposedmodel to be helpful to the case study is to make sure if itcontains the required activities and information flow forthe production system in CM environment. A panelof experts was formed from a pool of experiencedproduction planners, process planners, engineers andmanagers in the areas of production planning and controlin CM environments to validate the proposed model. Asurvey questionnaire was generated and used based onLikert scale to assess and refine possible strengthsand weaknesses of the model. The reliability of theinstrument was tested during the pilot study. A number offaculty members in the area of operations managementare involved. The pilot questionnaire contained was sentto 25 faculty members. The data from the pilot studywere gathered and a Cronbach’s Alpha test, a measure ofinternal consistency, was conducted. Results confirmedthat the instrument used in the pilot study was reliablewith a Cronbach’s score of 0.837.

The questionnaire developed in this study consistedof twenty-five questions. Seventy-five experts from theelectronics and telecommunication sector including thecase study staff were invited to participate in validatingthe proposed model. The responses were statisticallyanalysed using one-sample t-test. The analysis points outthat the experts feel the proposed model is comprehen-sive enough to be used as a reference model in a CMenvironments.

6. Conclusion

Because of today’s market competition and marketunpredictability, there is always a need for frequentCMS redesign. Indeed, system redesign or reconfigura-tion should be performed every time an orderedproduct needs to be manufactured, or, in the least, byshort planned periods of undisturbed production. Inorder to reach a practical CMS solution, it is necessaryto structure detailed design through a set of subsequentand interrelated activities aiming at solving differentdesign and operation problems. Such problems areclosely interrelated and must be solved together anditeratively. This paper developed a model for integratingprocess planning and production planning and control inCM that summarised the steps required to plan a prod-uct from the process design to the production order tothe customer delivery.

A four-stage methodology for the development ofthe model was followed, where work done by theindustry and academia was combined in a unique way.First, we gave a specific attention to Riezebos and


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Shambu’s contribution to production planning in CMand tried to modify it. Capacity planning functions,process planning functions, intra-cell organisation andcoordination, inter-cell organisation, and control andfeedback loops were designed in detail and were addedto this framework in order to enrich the planning sys-tem. Then, with respect to this framework, an integratedmodel based on IDEF0 for process planning andproduction planning and control in CM was developed.The completeness of the proposed model was validatedusing a panel of experts. The experts feel the proposedmodel is comprehensive enough to be used as areference model in CM environments.

Notes on contributorsAmir Hassan Zadeh is a PhD student inthe Management Science and InformationSystems Department in the Spears Schoolof Business at Oklahoma State University.He received his Master of Science degreein industrial and systems engineering fromAmirkabir University of technology,Polytechnic of Tehran, Iran. Prior to hisgraduate studies, he earned a Bachelor

of Science degree in applied mathematics. He has publishedresearch papers at international journals, conferenceproceedings and book chapters, also (co)authored severalbooks in Statistics and Probability, Operations Research andComputer Programming edited by the Sepahan and Rahian-Arshad Institutes, Iran. His current research interest is theuse of analytical modeling in operations management andinformation systems problems.

Hamid Afshari is a PhD student atMechanical and Manufacturing EngineeringDepartment, University of Manitoba,Canada. He received his Master of Sciencedegree from Amirkabir University ofTechnology, Tehran, Iran and his MBAfrom Industrial Management Institute,Tehran, Iran. He worked for IrankhodroAutomobile Manufacturing Industrial Group

for 9 years. His research interests are agent-based systems andnetwork optimisation in healthcare, manufacturing and supplychain.

Reza Ramazani Khorshid-Doust whoreceived PhD in Systems Engineering fromCase Western Reserve University (1991), afaculty member of Industrial EngineeringDepartment, Amirkabir University ofTechnology (Polytechnic of Tehran) since1992 till now, has supervised 115 mastertheses and PhD dissertations, published 28papers and 6 books, and received 45 grants

including 25 national ones.

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integration of process planning and production planning and control in cellular manufacturing

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