CIRP Journal of Manufacturing Science and Technology 2 (2009) 13–20

Process planning for IT-equipment remanufacturing

Sebastian Kernbaum, Steffen Heyer *, Stylianos Chiotellis, Gunther Seliger

Institute for Machine Tools and Factory Management, Technical University Berlin, Berlin, Germany

A R T I C L E I N F O

Article history:

Available online 21 August 2009

Keywords:

Remanufacturing

Process planning

Mathematical programming

A B S T R A C T

We present an approach for the design, evaluation and implementation of remanufacturing processes in

a given facility. Based on the description of the market situation and involved actors, a planning method

is derived. Data acquisition procedures for product, process and facility are described. A mixed integer

program is developed for optimization of a remanufacturing process and evaluation of its economic

viability. Additionally, the paper describes the technical implementation, the software workflow and

example application on the product category Flat Screen Monitors.

� 2009 CIRP.

Contents lists available at ScienceDirect

CIRP Journal of Manufacturing Science and Technology

journal homepage: www.elsev ier .com/ locate /c i rp j

1. Introduction

Reuse and Remanufacturing of Waste Electrical and ElectronicEquipment (WEEE) are a matter of current concern, driven byeconomic, ecologic, social and legislative factors. The potential thatlies in the reuse and remanufacturing of IT-equipment is not fullyexploited yet. Only a few specific products have been considered –e.g. mobile telephones [1–4] – and not all treatment opportunitiesavailable are applied. Moreover the financial uncertainties concern-ing product quantities, types and conditions that are long associatedwith remanufacturing processes limit the entrance of new actors intothe sector. Although planning decisions highly influence theefficiency of a production system carrying out remanufacturingoperations, decision support and planning tools, which are standardin assembly industries, are seldom available and applied. The needfor such tools is evident. Based on a market analysis and theidentification of actors that are aiming to extend their operations byestablishing remanufacturing processes as value adding processes,an integrated planning system is presented in this paper.

2. Actors involved and task definition

Actors involved in closed-loop-economy and their relation isgiven in Fig. 1, not considering legal aspects. The actors vary inaccess to product and material condition, amount and informa-tion’s about these. The following are identified as capable to extendtheir operations with remanufacturing oriented value addingprocesses: OEM’s, suppliers, maintenance shops, existing rema-nufacturing companies, and partly recycling companies.

These actors have in common the access to functional or non-functional products and components that are valuable enough to

* Corresponding author.

E-mail address: sheyer@mf.tu-berlin.de (S. Heyer).

1755-5817/$ – see front matter � 2009 CIRP.

doi:10.1016/j.cirpj.2009.07.003

justify their upgrade, through some remanufacturing treatment, toa marketable state or condition.

The same actors differ in their specific knowledge on theproduct itself, the products status and condition as well as theiroperational capability to bring it to a valuable condition. They alsodiffer in available equipment, processes and capacities, i.e. inremanufacturing capabilities. This raises the following questionsfor each specific actor:

� To what extent do I incorporate remanufacturing activities in myexisting facility/facilities?� Which specific remanufacturing processes am I able to carry out?� How much investment is needed in order to offer high quality

remanufacturing?� What are my specific costs and revenues once the remanufactur-

ing processes are operational?

To answer these questions in a suitable manner, a three stepplanning approach has been developed, implemented in a softwaretool and applied to the example of flat screen monitors remanu-facturing.

3. Planning method

The proposed approach involves three steps: the data analysis,the process design phase and the remanufacturing processoptimization of the remanufacturing tasks phase.

3.1. Data acquisition

The product and facility relevant data that are required for theproposed planning approach are determined and acquired.

Data regarding the product need include the product structure,i.e. components and component groups, joining elements andtechniques, disassembly sequences, material ratios etc. and end-

Fig. 1. Complexity in remanufacturing [6].

S. Kernbaum et al. / CIRP Journal of Manufacturing Science and Technology 2 (2009) 13–2014

of-life data (disassembly times and costs and recycling quota). Forease of system integration, product models are developed usingthe commercially available software system ProdTect [7]. ProdTectis a software tool which supports the development of ecologicallysound products by providing information related to a product’streatment and recycling at an early product development stage [8].In the ProdTect product model input module, the productstructural information is composed of:

� Parts information, such as material composition, disassemblymovement, dimension, shape, accessibility.� Connection information composed of the different joining

elements in the product.� Priorities information, which gives an order of the parts inside

the product. A part is prior to another if it needs to be dismantledto get access to the other.

ProdTect calculates technical, economic and ecological para-meters. The resulting data, such as disassembly times andsequence, can then be utilised for the planning of the end-of-lifeprocesses for a product [9]. An overview of the software toolProdTect is given in Fig. 2.

Product accompanying information were analyzed and pre-pared for being used for the proposed planning approach.

The next step involves acquiring data regarding the resourceand capacity planning of the given facility. Such data include theavailable installed capacity, the actual job schedule and theinventory levels and can be acquired from the ERP (EnterpriseResource Planning) system of the facility. Facility accompanyingdata were analyzed and prepared for application in the proposed

planning approach in accordance to the VDI 3633 guideline ([10],Fig. 3).

3.2. Process design

The second planning step is the development of the processmodel. The process model design determines all possiblesequences and types of remanufacturing steps that are requiredin order to process a batch of incoming products, e.g. testing,cleaning, disassembly, reassembly from a specific product type, e.g.flat screen monitors. The sequence is derived by conducting trialruns on a number of sample products. A graphical user interface(GUI) has been developed in order to assist the planner to visualizethe developed remanufacturing process in the form of a network.This network acts as the interface of the database that contains theproduct, process and facility information.

Fig. 4 gives an overview of the structure in the example of atypical remanufacturing process. Products entering are firstexamined according to product relevant testing criteria. Basedon these tests, a list of failures can be documented for each specificproduct. These lists of failures need to be treated to bring theproduct back to a valuable condition—they therefore createspecific ‘‘remanufacturing paths’’ for each single product in theoverall designed process network.

Based on results of preliminary tests, treatment decisions aremade: if the amount of failures exceeds a threshold of acceptablefailures in the designed process, the product is sent to materialrecovery processes. In the case where a product is in a condition tobe sold to customers, only cleaning and packaging operations needto be carried out. If failures are worth to be treated, the product is

Fig. 2. ProdTect overview.

S. Kernbaum et al. / CIRP Journal of Manufacturing Science and Technology 2 (2009) 13–20 15

send to a first disassembly operation. Information available fromProdTect (e.g. disassembly times and costs) is connected to thisoperation and further information needed for the planningapproach can be added by means of the GUI, e.g. stationassignments.

3.3. Remanufacturing process optimization

The objective of the third planning step is to determine whethera batch of incoming products is to be commissioned forremanufacturing, i.e. whether the remanufacturing of a certainnumber of products of a certain type is of economical interest for agiven facility and to what extent the remanufacturing processeswill be carried out. This implies that there are a variety of optionsto be examined; fully refurbish, partly refurbish, recycle etc. Amixed integer optimization program (MIP) has been developed toassess the economic feasibility of processing the batch of theincoming products under given capacity situation of the facility.The objective of the optimization is to maximize the profit ofremanufacturing the incoming batch under constraints of capacity

Fig. 3. ERP system data structure.

availability (workers and machines), operational costs, productflow, product condition, inventory levels, transportation costs andadditional capacity investments that may be required. All relevantdata for the optimization model are provided from the productmodel, the process model, the ERP system of the facility and theinput of the planner regarding cost related parameters. Especiallyfor the condition of the incoming products, the planner can selectbetween using available historical data or an estimate based on hisown experience. A strategic decision of the available budget to beallocated for additional capacity investments needs to be takenbeforehand. Based on the solution of the model, the planner candecide whether the available batch of products is to be acquired ornot and determine the optimal number of steps of the remanu-facturing process.

The remanufacturing process has been modelled in remanu-facturing steps which are arranged in seven categories Type (1, . . ., 7)respectively: test steps, reassembling, disassembling, steps thatrequire additional parts to be purchased and access to thewarehouse, sale steps after which products can be sold to generateincome, the entrance steps (product entrance) and finally generalremanufacturing steps. This categorization is executed by theplanner (the planner defines which steps belong to each category)at the beginning of the optimization and is required due to specialproduct flow constraints that accompany the different types ofsteps. In addition, it should be mentioned that our model does notdifferentiate between a product to be remanufactured, a part or acomponent.

The following set notation is used in the remainder of the paper:

I ¼ f1; . . . ; ig; i2N� : remanufacturing ‘‘step’’; (1)

This set includes all remanufacturing steps. The various steptypes (and thus corresponding subsets) are defined with the use ofthe binary parameter:

Type ð1; . . . ;7Þi ¼ 1 if step i belongs to category 1; . . . ;70 otherwise

�;

i2 i;

(2)

W ¼ f1; . . . ;wg;w2N �workstations (3)

The decision variables that are used are shortly explained:NPLij, NPTIi, NPTOi, i 2 I respectively denote the number of

products that are between two remanufacturing steps i and j, thenumber of products at step i before performing the remanufactur-ing task and the number of products at step i after theremanufacturing task is performed. NPTSi stand for the numberof parts required from storage for step i where i 2 {i 2 I: Type4i = 1},NPGSi for the number of parts returned to the storage after step i

and variables NPSFi denote the final storage level after step i,where i 2 {i 2 I: Type4i = 1}. NPPi denote the number of additionalparts/components that need to be purchased for step i 2 {i 2 I:Type4i = 1}. Variables NNWSw illustrate the number of additionalworkers to be assigned to workstation w while NNSw the numberof new workstations to be installed. Finally, NTi denote the numberof batches of parts/components to be purchased and NMCi are usedfor modelling convenience and stand for the number of maincomponents to be reassembled in a reassembly step. All decisionvariables are restricted to take values from the set of non-negativeintegers.

The following parameters have been used in the model:

PFBi; j ¼1 if the transition from step i to step j is allowed

0 otherwise

�;

i; j2 I;

(4)

cess design (simplified).

S. Kernbaum et al. / CIRP Journal of Manufacturing Science and Technology 2 (2009) 13–2016

BOMi ¼

1=Xk

1

PFBk;i; 8 i2fi2 I : Type2i ¼ 1g; k2 I

Xj

1

PFBi; j; 8 i2fi2 I : Type3i ¼ 1g; j2 I

1; otherwise

8>>>>>><>>>>>>:

; (5)

Fig. 4. Procedure for pro

max

Xi

NPTOi � SalePi

�X

w

HRw � ðX

i

OPTi �WCBi;w � ðNPTIi � ð1� Type2iÞ þ NPTOi � Type2iÞÞ

�X

w

ððNNWSw þ NWSw � ð1� LwÞÞ � CWw � CapaW � DDÞ

�X

w

CSw � NNSi

�X

i

NPPi � CPNi

�X

i

CTN � NTi

8>>>>>>>>>>>>>>>>><>>>>>>>>>>>>>>>>>:

9>>>>>>>>>>>>>>>>>=>>>>>>>>>>>>>>>>>;

I;w2W (6)

Parameter (4) indicates the allowed step sequences, i.e.whether the transition from remanufacturing step i to remanu-facturing step j is meaningful, while parameter (5) is used to modelthe different flow conservation behaviors of the various remanu-facturing steps types. Some steps result in a change in the numberof product, i.e. a disassembly step would result in an increase in thenumber of products while a disassembly would result in itsdecrease thus different step types need to be addressed explicitlyin the model.

The objective function (6) maximizes profit, i.e. maximizes thesum of income from the process minus the sum of relevant costs. Pi

is the sale price of each product after completing step i where, CPNi

the cost of purchasing a new part, CW the labour cost per workerper hour, HRw the machine hour rate for every workstation w, CTNi

the transportation cost per batch of purchased parts for each step i

that requires parts to be purchased, NTi number of batches ofpurchased parts for each step i and CSw the cost of a newworkstation. The MIP model follows (6)–(23):

Subject to:

NPTIi ¼Xk

1

NPLk;i � PFBk;i 8 i2fi2 I : Type6i ¼ 0g; k2 I

NPSIi; otherwise

8><>: (7)

NPTOi ¼ NPTIi � BOMi; 8 i2 I; (8)

turing Science and Technology 2 (2009) 13–20 17

Xi

ðNPLi; j � PFBi; jÞ ¼

NPTOi þ ðNPTSi þ NPPiÞ;i2fi2 I : Type4i ¼ 1

and Type5i ¼ 0g;NPTOi; i2fi2 I : Type5i ¼ 0g

8>><>>: 8 i; j2 I; (9)

NPGSi ¼ NPTOi �X

j

ðNPLi; jÞ � NPTSi � NPPi;

8 i2fi2 I : Type4i ¼ 1g; j2 I; (10)

NPPi �MaxPPi; 8 i2 I; (11)

NPLi; j ¼ NPLi; j � PFBi; j 8 ði; jÞ 2 I � I;NPLi; j ¼ NPTOi � PTi; j;

(12)

8 ði; jÞ 2 fi2 I : Type1i ¼ 1g � I;NMCi ¼ NPLk;i;

(13)

8 ði; kÞ 2 fi2 I : Type2i ¼ 1g � fk2 I : Maink ¼ 1g;NPLk;i ¼ NMCi � PEBk;i;

(14)

8 ði; kÞ 2 fi2 I : Type2i ¼ 1g � I;

NPLi; j ¼NPTOi � PFBi; j

BOMi;

(15)

8 ði; jÞ 2 fi2 I : Type3i ¼ 1g � I; (16)

Xi

OPTi �WCBi;w � ðNPTOi � Type2i þ NPTIiÞ � ð1� Type2iÞ

� CapW � DD � ððNWSw þ NNWSwÞ � NWSw

� LwÞ; 8w2W ; i2 I; (17)

NWSw þ NNWSw � ðNESw þ NNSwÞ �MaxWSw; 8w2W ; (18)

NPSFi ¼ NPSIi þ NPGSi � NPTSi; 8 i2fi2 I : Type4i

¼ 1 and Type6i ¼ 0g; (19)

NPTSi � NPSi; 8 i2fi2 I : Type4i ¼ 1g; (20)

NTi �MaxPTi�NPPi; 8 i2fi2 I : Type4i ¼ 1g; (21)

NPTSi;NPGSi;NPSFi;NPPi;NNWSw;NNSw;NTi;NMCi 2Zþ; (22)

NPLi; j;NPTIi;NPTOi 2Rþ: (23)

The first group of constraints (7)–(16) addresses the flow ofmaterial through the process. Constraints (7) are flow conservationconstraints that hold for all type of steps and ensure that thenumber of products in step i before performing the task is equal tothe sum of all products transferred there from all possible previoussteps k. Especially for the entrance step (Type6) of the process it isassumed that the number of products is equal to the initialwarehouse level. Constraints (8) ensure that the flow of products isconserved according to the type of remanufacturing step.Constraints (9) guarantee that the number of parts needed forstep i is provided by predecessing steps, parts in storage orpurchased parts. Constraints (10) are valid for steps that are able topurchase parts and have access to the warehouse (Type4) anddetermine the amount of products/parts to be returned to storageafter the execution of the step. In addition, (11) limit the number ofparts that can be purchased per Type4 steps to MaxPPi; since weare dealing with obsolete IT equipment as remanufacturingproducts, it is not rare that the supply of parts and componentsis limited. Eq. (12) determine the allowed transitions from step i tostep j. Constraints (13) address test stations (Type1) and definetheir product output, i.e. number of products that have past or

S. Kernbaum et al. / CIRP Journal of Manufac

failed the test, according to the parameter PTi,j which denotes thepercentage of products to be transferred from step i to step j wherestep i is a testing step. In the case of reassembly steps i (Type2), thenumber of products that are identified as the main component(NMCi) needs to be matched by all other required components thatare coming into the step. This is ensured by constraint (15) whichidentifies the main part of the reassembly operation and constraint(14). Parameter Maink = 1 is used to identify the product or partthat will be considered as the main part in the reassembly step(Type2). In the case of disassembly steps (Type3), the number ofproducts on the exit of the step increases since we obtain morecomponents. Eq. (16) applies the corresponding flow constraints.

The next group of constraints addresses capacity restrictions.More than one step can be executed in one workstation; the binaryparameter WCBi;w (see constraints (17)) determines whether step i

can be executed in workstation w. Constraints (17) ensure that thesum of the time required in order to carry out all steps assigned to aworkstation w, does not exceed the capacity of the station.Capacity, occupied by other jobs beside the planned, is addressedwith Lw. It also tackles capacity extensions by hiring additionalworkers or by investing in new workstations. Here NWSw denotesthe number of existing workers assigned to the station and CAPWw

each workers capacity in pieces per hour. Constraints (18) impose abound (MaxWSw) on the total number of workers that can beassigned to a workstation. This expresses possible limitations ofspace or lack of necessary tools per workstation.

Constraints related to the warehouse include Eq. (19) where thestorage level after completing step i is forced to be consistent withall product flow regarding the warehouse, i.e. flow that originatesor is directed to steps i that have access to the warehouse (Type4).Constraints (20) ensure that the number of parts drawn from thewarehouse is at most equal to the actual warehouse level.

The set of Eq. (21) imposes that the number of parts/components to be purchased is limited to the transportationcapacity. Here MaxPTi is the maximum number of parts orcomponents that can be transported per order. Note that eachType4 step i is related to specific parts/components which havevarious properties and dimensions thus different maximumquantities that can be transported per batch.

Besides maximum profit as a result of the objective function,the following data can be extracted after calculations:

CostP ¼X

i

NPPi þ CPNi þX

i

CTNi � NTi; 8 i2fi2 I : Type4i ¼ 1g

(24)

CostW ¼X

w

CSw þ NNSw; 8w2W (25)

CostPro ¼X

w

HRw � X

i

OPTi �WCBi;w � ðNPTIi � ð1� Type2iÞ

þ NPTOi � Type2iÞ!8w2W ; i2 I (26)

NumberW ¼X

w

NNWSw; 8w2W (27)

LabourCost�w ¼ ðNESw þ NNSwÞ

�

Xi

OPTi �WCBi;w�

ðNPTIi � ð1� Type2iÞ þ NPTOi � Type2iÞ

0@

1A;

8w2W ; i2 I (28)

ring Science and Technology 2 (2009) 13–20

LabourCost ¼X

w

LabourCost�w; 8w2W (29)

UtilWw ¼1

ðNNWSw � NWSwÞ � Ca pWw � DD

�(

NWSw � CapWw � DD � Lw

þ

Xi

OPTi �WCBi;w�

ðNPTIi � ð1� Type2iÞ þ NPTOi � Type2iÞ

0@

1A);

8w2W ; i2 I (30)

UtilW ¼P

w UtilWw � ðNNWSw � NWSwÞðNNWSw � NWSwÞ

8w2W (31)

UtilSw ¼1

ðNESw � NNSwÞ � CapWw � DD �MaxWSw

�(

NWSw � CapWw � DD � Lw

þ

Xi

OPTi �WCBi;w�

ðNPTIi � ð1� Type2iÞ þ NPTOi � Type2iÞ

0@

1A);

8w2W ; i2 I (32)

UtilS ¼P

w UtilSw � ðNESw � NNSwÞðNESw � NNSwÞ

8w2W (33)

S. Kernbaum et al. / CIRP Journal of Manufactu18

Fig. 5. Software im

Eqs. (24)–(28) deal with accrued costs due to the process. CostP asthe cost for purchasing bought-in parts and there transportation isaddressed in (23). Cost for new substations for all workstations isCostW (25). As the result of process time per part and hour rate HRw

for each workstation w, the process cost for all substations is CostPro

(26). The number of workers in total NumberW is the sum of all newworkers on every workstation is addressed in (27). Following theprocess cost in (26), the labour cost LabourCost�w in (28) is theprocess time for one part times the number of parts on each step foreach workstation. As shown in (28), labour cost LabourCost in total isthe sum over w of the labour cost for each workstation w.

Eqs. (29)–(33) address the utilisation of workers and work-stations. In (29), UtilWw is the utilisation of workers on eachworkstation w as the result of dividing process time, process timeper part times number of parts, by available time as the result ofnumber worker time available in days for the remanufacturing job.Time, occupied by other jobs besides the planned one is consideredtoo. The utilisation of all workers UtilW on average UtilWw is theutilisation for each workstation, assess by the number of worker.According the workers, the workstation-utilisation UtilSw of eachworkstation w in (31) is the process time divided by the availabletime. In that case, the available time is calculated by the number ofmaximum worker per substation times number of substationstime available time. UtilS as the average utilisation of everyworkstation, assess by the number of substations for eachworkstation is handled in (33).

plementation.

Fig. 6. Operations flow.

S. Kernbaum et al. / CIRP Journal of Manufacturing Science and Technology 2 (2009) 13–20 19

4. Implementation

The approach presented was implemented in a software tool,shown below in Fig. 5.

Active Server Pages ASP.NET 2.0 technology is chosen for thedevelopment of the software because of its data managementabilities with ActiveX Data Object .NET technology and easy excessto SQL databases. The Software is hosted on a Microsoft WindowsServer system and is operable online. This allows operating systemindependent application and multiple user abilities through theWorld Wide Web. For data storing and transaction Microsoft SQLServer 2005 was applied due to its common language runtime

Fig. 7. Input of proces

(CLR) component for Microsoft .NET. The .NET language VisualBasic .NET is used for developing the graphical user interface on theserver. Following the general work flow, see above in Section 3,planning, calculation and result presentation is shown in Fig. 6.

Starting with Step #1 the company, product and available timefor the planned job (hours per day and available days) has to bedefined as general data. For each workstation, name, number ofcurrent substations, number of maximum worker per substation,number of current worker per substation, prize per substation,occupation by other jobs (basic load), labour cost and process costper hour for each workstation has to be specified. The neededinformation for bought-in parts is name, number of available parts,costs for transportation per lot, lot size and cost per part. All thesedata are entered menu-driven.

Second step is the process plan. Based on the before designremanufacturing process and based on the presented mathematicalgorithm, the process has to be entered. The process will behandled as a net, made from connected single process steps. Thedata are divided in process and linked general data.

Process data consist of:

� Name and type of the process step,� process time per step per piece,� related workstation to each process step,� initial number of parts per step,� error distribution for material flow splitting and� income per piece.

All data have to be entered and modified for each step. Stepinterconnections and presentation are handled in the drag anddrop capable process editor via moving single steps close together.Necessary data depends on the step type (see above Section 3.3,categories types) and are presented independently for each process

s step parameter.

S. Kernbaum et al. / CIRP Journal of Manufacturing Science and Technology 2 (2009) 13–2020

step. For example a general step is distinguished by name, processtype, process time and related workstation, as shown in Fig. 7. Forclarity, colors are used to indicate different process types. The thirdstep is totally handled by the application. Collecting all relevantdata from the database and parsing these for the external solverapplication AIMMS will be done autonomously after starting thecalculation process. After calculating the objective function, therelevant data are culled from AIMMS and saved in the database. Atthe final step, all in Section 3.3 announced results are presented tothe user in table form. As a calculation result, not every processstep is needed to achieve the max profit. Therefore, theremanufacturing process will be presented for the uses. Idle steps,characterized by no flow of parts in and out, are colored in gray.

5. Example application

Flat screen monitors have been selected for various reasons; themassive production volumes, increasing demand and continuoustechnological innovations that introduce new generations ofproducts create a steady stream of obsolete products that requireremanufacturing. The models developed have been tested onproblem instances that have been created based on the experienceof industrial partners. The introduced software was validated withSensitivity Analysis, special Input Testing and Fault/FailureAnalysis on small example processes to determine the behaviorof each model element. A typical problem instance for flat screenmonitors remanufacturing consists of approximately over 200remanufacturing and process steps. Implementation of theremanufacturing process into the software took about 30 min,the result calculation on a moderate computer system less than30 s. Starting from the mathematic algorithm, relevant product,process and company parameters were identified for evaluatingremanufacturing processes. Four companies were modelled withcase studies due to their business model. Company A is specializedon disassembly of WEEE goods in small numbers. The relationshipbetween number of flat screens for remanufacturing and profitableinvestment was analyzed. How many flat screens are needed forprofitable investment in sophisticated remanufacturing work-stations was investigated. Company B is specialized in remanu-facturing small numbers of all kinds of WEEE goods. Withoutequipment for an initial test for flat screens, error detection is notpossible. In this case, the increase of vertical integration whenadding an initial test was analyzed. Company C handles largenumbers of computers, flat screens, printers and other electronicoffice equipment for remanufacturing. Unlike the other companies,C is not dealing with profound errors and its utilisation is close to100%. The value of remanufactured equipment, e.g. flat screen,decreases in time [12]. In following this behavior, C wants to dealwith about 1500 entities in addition. It was learned that neitherbuying the need number of workstations to finish the additionaljob as soon as possible nor handling the job with the given

equipment was most profitable. Using simulation techniques tohandle this case study, the adapted configuration of impairmentand investment was found. Company D represents a plant thatresulted from a research study, which is specialized on semiautomated flat screen remanufacturing [5]. The implementation ofthis plant, adapted to the developed algorithm was studied andprofit could be expected for 300 flat screens per day. The casestudies represent general applications for the presented approach.Beside the prediction of profit, increase of value adding could beshown for each case.

6. Summary and outlook

A planning approach for remanufacturing process design andevaluation was presented. It is based on a three step approachwhich has been integrated into a single user-friendly softwareenvironment and exemplarily applied to the case of flat screenmonitors. The design of the mathematical platform is modular inorder to allow for different solver configurations and expansionmodules in the future. The proposed approach is productindependent and can be easily adapted to address a variety of ITequipment. Future research will concentrate on extending theapproach to include a scheduling module that will apply theproposed remanufacturing process design to the actual productionschedule of the facility.

References

[1] Kharif, O., 2002, Where Recycled Cell Phones Ring True, BusinessWeek Online, .07-26-2002.

[2] Quinn, J., et al, 2002, Cellular 2002, A Study of the Worldwide CellularTelephone Market, Phoenix, AZ, USA.

[3] Seliger, S., Franke, C., Ciupek, M., Basdere, B., 2004, Process and FacilityPlanning for Mobile Phone Remanufacturing, Annals of the CIRP, 53/1.

[4] Franke, C., Basdere, B., Ciupek, M., Seliger, G., 2005, Remanufacturing of MobilePhones—Capacity, Program and Facility Adaptation Planning, Omega—TheInternational Journal of Management Science, 33.

[5] Franke, C., 2006, Beitrag zur Steigerung der Nutzenprodukti-vitat von Ressour-cen durch Anpassungs-programmplanung am Beispiel von Flachbildschirmen,Dissertation Technische Universitat Berlin.

[6] Takata, S., Kimura, F., van Houten, F.J.A.M., Westkamper, E., Shpitalni, M.,Ceglarek, D., Lee, J., 2004, Maintenance: Changing Role in Life Cycle Manage-ment, CIRP Annals—Manufacturing Technology, 53/2: 643–655.

[7] Herrmann, C., Frad, A., Revnic, I., Luger, T., 2005, Product Architect, a NewApproach for Transparency and Controlling of the End-of-Life Performance, in:Proceedings of the EcoDesign2005 (Tokyo), .

[8] http://www.prodtect.com, last access: 13.11.2007.[9] Hesselbach, J., Herrmann, v.C., Westernhagen, K., 1999, Datenbanken als

Informationstrager von der Produktentstehung bis zur Demontageplanung,in: Proceedings of ‘‘Umweltinformatik zwischen Theorie und Industrieanwen-dung’’, 13th International Symposium (Magdeburg), .

[10] VDI Guideline 3633: Simulation of systems in materials handling, logistics andproduction—Fundamentals, (2000), Beuth Publishing House.

[12] Scheidt, L.-G., 2007, Value Analysis PCs, Notebooks and Monitors for Reuse,Refurbishment and Trade-in, in: Proceedings of the eco-X ‘‘Conference Sustain-able Recycling Management & recycling Network Centrope’’ (Wien, Austria), .