A scheduling system for IC packaging industry using STEP enabling technology

256 IEEE TRANSACTIONS ON COMPONENTS, PACKAGING, AND MANUFACTURING TECHNOLOGY—PART C, VOL. 20, NO. 4, OCTOBER 1997

A Scheduling System for IC Packaging IndustryUsing STEP Enabling Technology

Thu-Hua Liu, Amy J. C. Trappey, and Fu-Wei Chan

Abstract—In this decade, semiconductor-based electronic in-dustry has grown rapidly and prospectively. The packagingtechnologies of electronic elements are also matured in support-ing the development of electronic products, which tends to getsmaller in size with higher capacity and resolution. In order toincrease packaging quality and reliability as well as to reduce thepackaging cycle time, not only advanced packaging processes andtechniques but also efficient production management methodsneed to be developed. Among production management, schedul-ing is one of the most important tasks to ensure the performanceof competitive manufacturing capability. This research develops acomputer-aided scheduling system (CASS) for integrated circuit(IC) packaging industry. The standard for the exchange of prod-uct model data (STEP) enabling technology is adopted to modeland implement the system. The effort aims to achieve integrationof engineering applications by standardizing the modeling and theuse of product data. This paper uses IDEF0 to model the IC pack-aging scheduling process and EXPRESS language to define thedata models. The IC packaging scheduling system is implementedin an integrated environment using the object-oriented language(C++) and an object-oriented database. The ST-Developer isused as the kernel to interface the application language, thedatabase, and the EXPRESS data models. The architecture ofthis integrated implementation environment is not only effectivefor scheduling task but also useful in general applications forproduct design, analysis, and production planning.

Index Terms—Computer-aided scheduling system (CASS),EXPRESS, IC packaging, object oriented database, scheduling,STEP.

I. INTRODUCTION

SINCE 1980’s, the semiconductor-based electronic industryhas grown rapidly and prospectively, particularly in Asia

countries such as Japan, Taiwan, South Korea, and Singa-pore. Nowadays, the high functional electronic products aredesigned with reduced size and light weight features, which arecomplemented largely by electronic packaging industry. Thesemiconductor packaging is steadily progressed toward thefine pith, high pin count, multi-chip, and diversification, whichfulfill the integration requirements of electronic products. Wu[1] reports that, in the next five years, Taiwan will invest

Manuscript received November 1996; revised October 13, 1997. Thiswork was supported in part by the Taiwan National Science Council underGrant NSC-2212-E-186-001. This paper was presented in part at the ASMEInternational Engineering Congress and Exposition, Atlanta, GA, November17–22, 1996.

T.-H. Liu is with the Department of Industrial Design, Chang GungUniversity, Tao-Yuan, Taiwan, R.O.C.

A. J. C. Trappey and F.-W. Chan are with the Department of IndustrialEngineering, National Tsing Hua University, Hsinchu, Taiwan, R.O.C.

Publisher Item Identifier S 1083-4400(97)09331-5.

approximately ten billion U.S. dollars in the semiconductormanufacturing industry and will push the electronic packagingindustry into another surf.

The manufacturers of integrated circuit (IC) packaging,which is one of the downstream areas of semiconductorindustry, concentrate their efforts on reducing the packagingcycle time and increasing packaging quality and reliability.To accomplish the above objectives, not only the advancedpackaging processes but also efficient production managementtechniques need to be developed. Nonetheless, to perform highcompetitive manufacturing capability, “scheduling” is one ofthe most important functions in a production managementsystem. Production scheduling aims to assign the startingdates and due dates for the parts to be processed throughthe manufacturing resources. Two major factors make thescheduling a complex task. First, the number of orders andtypes of parts may run in hundreds simultaneously. Second,each part has its own process routing that may need to runthrough dozens of machines. In a real production environ-ment, the number of machines and equipments, with differentfeatures and capacities, is often limited. Thus, optimizingmanufacturing scheduling becomes a primary goal and a toughtask of production management.

A manufacturing system often involves tremendous in-formation, to process all related information and generatea manufacturing schedule by production engineers is timeconsuming and inefficient. Thus, a computer-aided schedulingsystem (CASS) can solve the above problems and providea more consistent and better scheduling decision. In thetrend moving toward CIM implementation, an integratablecomputerized scheduling system is the key to the concurrentengineering practice.

Enterprises nowadays maintain a lot of data in differentdatabases for different application systems, e.g., the productdefinition in a CAD database and process plans in a productionplanning database. Application programs have always sufferedfrom the problem of dissimilar data structures among variouscomputer packages. An information model is needed to definethe data relevant to the products and their manufacturingresources. Thus, data can be easily accessed and integratedwithout redundancy.

On the other hand, in the direction toward concurrent engi-neering, many efforts have been devoted to the availability ofa consistent information source that can be used continuouslythroughout a product life cycle. This is the objective fordefining the standard for the exchange of product model data(STEP) [2]. The main goal of STEP is to develop a neutral

1083–4400/97$10.00 1997 IEEE

LIU et al.: SCHEDULING SYSTEM FOR IC PACKAGING INDUSTRY 257

specification for sharing life cycle information of products.STEP is independent to any computer systems and languages.To enable correct decision making from corresponding data,there is a need to develop an information model to describeand capture the information of manufacturing resources andprocesses (such as customers, orders, work-in-processes, work-ers, stations, and machines). These information is necessary tosupport concurrent engineering applications.

This paper describes a CASS for IC packaging industry. ICpackaging contains three major processes:

1) separating the chips from the wafer;2) connecting wires between each chip and the lead frame;3) molding the IC chips.

The IC packaging provides the functions of protecting the ICdevice, making IC chip easily mounted on PC boards andconducting the heat generated by the device. There are twotypes of IC packaging, namely ceramic and plastic. Most of thecommercial IC chips use plastic packaging. The manufacturingprocess of plastic packaging contains the following steps:

1) die sawing;2) die mounting;3) wire bonding;4) molding;5) trimming and forming;6) marking;7) plating;8) testing.

The process layout of the IC packaging factory describedin this paper is a flow line type as the setup of most of ICpackaging plants. The scheduling principle of the factory isbased on the sequential due dates of orders. The first step of thescheduling is to revise the forecasted capacity of the followingday on the schedule. A production planning engineer revisesthe forecasted capacity based on the capacity limitation of eachstation and the works-in-progress (WIP’s) of the productionline. Then, the planner can decide the production quantityof the next day on the schedule. Further, the planner checksquantities of WIP’s in the die mounting and wire bondingstations, which are the bottle neck stations. Then, the actualreleasing quantity of the next day is determined. Finally, theplanner obtains the new schedule of the next week and thereleasing quantity per day of the week.

Manufacturing systems are complex. Different types ofdata representing machines, workers, and other resources areinvolved in a scheduling system. This research intends todevelop a computer-aided IC packaging scheduling systemin which its information model is developed by EXPRESSlanguage. The main function of the system is to schedulethe orders so that rearranging the machines and workersand revising the due dates asked by customers can be moreefficiently and accurately achieved.

II. L ITERATURE REVIEW

Production scheduling has been studied for the past fewdecades. A large amount of literature have been published inthis area. However, many researches have concluded that thereis a gap between theoretic progresses and industrial practices

[3]. Dudeket al. [4] comment on the lack of real applicationsusing the huge amount of research results. They observe thatapplying flowshop sequencing to industrial activities will be afuture direction to go. Scheduling is a difficult and complextask in a production system which constraints, resources,and timing assume particularly significant roles. Frequently,a production planner needs to evaluate and balance a largeamount of interacting factors in the search for an optimum. Ithas long been recognized that practical scheduling problemsare computationally too complex to be handled by purelymathematical techniques. There are three categories of thecomputer-based scheduling approaches [5]

1) simulation techniques (e.g., queuing network models,discrete simulation models, and perturbation analysismodels);

2) optimization techniques (e.g., dynamic programming,branch and bound, linear programming, integer program-ming, and PERT);

3) artificial intelligent or knowledge-based techniques.

Most of the existing scheduling techniques are based onsome algorithmic descriptions of the scheduling task, whichusually described by resources, objectives, and constraints.Some forms of mathematical-optimizations or algorithmic-programming techniques are then used to determine the op-timal assignment of resources. Therefore, goals and objectivesare achieved within the stated constraints [6]. Much of thework is surveyed in Graves [7]. Before the early 1980’s, themethodologies in many articles are based on mixed-integermethods, combinatorial optimization and integer programming[8]. However, the algorithmic approaches do not considermany of the practical issues involved. In particular, the con-ventional model cannot easily handle multiple objectives (e.g.meet due dates and minimize costs) and constraints whichshould be considered in practical problems.

Knowledge-based techniques can solve some of the aboveproblems and can incorporate practical rules-of-thumb into thescheduling process. However, a completely knowledge- basedsolution to these problems is not yet possible and there aremany theoretical issues still need to be addressed. There aretwo general trends in the research of AI-based planning andscheduling systems [9]:

1) a trend away from general-purpose systems and towardthe incorporation of increasingly specific knowledgeabout the problem area [10], [11];

2) a trend away from automated plan generation and towardsystems that provide intelligent help to planners [12],[13].

WIP inventory plays a very important role in productionscheduling. It has drawn a great deal of attention from re-searchers. Conwayet al. [14] study the effects of WIP inserial production lines. Burmanet al. [15] investigate therelation between the WIP level and the system performanceof integrated circuit manufacturing lines. Recently, schedulingresearches focus on the front-end processes of semiconductormanufacturing industry, primarily because of the complex pro-duction management and the expensive facilities of front-endprocesses. Wu [16] develops a scheme of testing production


planning and control for a short production interval. Thereare few researches discussing the scheduling of IC packagingproduction.

Scheduling of manufacturing systems in industrial practicecan be viewed as a hierarchical decision process. At thehigher level, materials requirement planning (MRP) and masterproduction scheduling (MPS) systems translate the demand forproducing products into projections of required resource ca-pacity and estimations of production lead-times. These systemsusually ignore capacity constraints. Their outputs are a set ofjob orders with corresponding lot sizes, “ideal” starting datesand due dates. At the lower level, detailed, or short intervalscheduling (SIS) is, then, required to perform the assignmentand sequencing of job orders to production resources. Thisactivity has to consider the finite capacity of the manufacturingsystem and the dynamic factors, such as machine break-downs.

An early reference to the modeling of manufacturing in-formation is in the IMPPACT project documentation [17].IMPPACT defines a Factory Model that structures the infor-mation for the facilities such as machine tools, fixtures, androbots. Further, IMPPACT also defines a Process Model thatconsists of information describing the production activitiessuch as processes, operations and passes. A ManufacturingResources Model [18] represents the whole factory, whichincludes machine tools for various manufacturing processes,tools, jigs, fixtures, control devices, communication equip-ment, materials, buildings, and human resources. Project 2 ofthe ISO/TC184/SC4/WG8 [19] aims to develop generic andimplementation-oriented standards that enable enterprises todocument resources and entire manufacturing processes, tocommunicate internally and externally, and to optimize theirResource Usage Management. This project collaborates withother standardization bodies to develop an application-orientedrepresentation of Resource Usage Management informationand function. Molinaet al. [20] point out that providinga consistent source of manufacturing information to bothusers and applications is a key to a successful concurrentengineering. An information model named “ManufacturingModel” is designed as a key element of a prototyping researchsystem called the Model Oriented Simulations EngineeringSystem (MOSES). This information model is defined usingEXPRESS language and developed using Booch’s object-oriented methodology [21].

Czerwinski and Sivayoganathan [22] define the problemsassociated with information storage and transfer in the creationof applications for a computer-aided engineering environment.They create a manufacturing model using the EXPRESS lan-guage that allows manufacturing decisions to be made basedon the availability of current resources. The paper proposesthe use of EXPRESS-G structure that allows various types ofSTEP users to access and query data files. Thus, the creation ofcomputer-integrated manufacturing applications can be easilyachieved. STEP standards support the methodologies andtechniques for product modeling through entire life cycleof the product. Liu and Fischer [23], [24] develop feature-based manufacturing applications using STEP methodologies.Qiao et al. [25] propose a STEP based product preparationprocedure for CAPP.

Fig. 1. Overview of the scheduling decision processes.

STEP is developed with an architecture of three layers,i.e., application, logical and physical. The application layerdevelops a number of reference models specifically for indi-vidual applications. The logical layer utilizes EXPRESS andEXPRESS-G to define entities and their relationships. Thislayer represents all data models in the form of “schema.”The physical layer provides a data structure for data sharingand communication [2]. The EXPRESS, Part 11 of ISO10303, has been published as an international standard in1994 [26]. The philosophy of EXPRESS modeling methodis based on the object-oriented concept. It is designed to meetthe STEP requirement and also is a powerful language forthe representation of complicated information structure. Thepurpose of using EXPRESS is to describe the characteristicsof information that someday might exist in an informationbase [27]. In the EXPRESS language, an entity is defined asa set of attributes. A data type can be a primitive such asnumber, real, string, or an entity (i.e., reference to anotherentity). The relationships between entities are subsumed in theentity data type or the domains of the attributes, in which theroles are represented by the names of the attributes. The entityor its attributes (and relationships) can be further described orrefined by constraints written in a procedural language form.Supertype/subtype hierarchy is supported with constraints onthe allowable combinations of subtypes.

III. PROCESSES ANDDATA MODELS

Fig. 1 describes an overview flow-chart of the schedulingsystem. Inputs of the scheduling system are categorized intosix groups:

1) order;2) WIP report;3) schedule report;4) production planning setup data;5) production system status;6) forecast capacity of the next day.

The first step of the scheduling system is to revise theplanning capacity of each product and calculate the daily


scheduling quantity of the next week. The planning capacityis inputted to the scheduling system for the schedule of thenext week. Checking the planning capacity whether it couldbe accepted by the production system. Then, the schedulingsystem calculates the daily scheduling quantity for the nextweek considering the status of the production system. Thestatus of the production system is calculated using the data ofWIP’s and scheduled works. This step is a rough-cut capacityplanning for the production planning.

The second step is to sequence all of the orders based ontheir due dates. We consider all of the orders received upto date. After calculating the daily scheduling quantity andarranging all of the orders, the third step is to pre-scheduleorders by the daily scheduling quantity. The objective ofthe pre-scheduling is to acquire the estimated delivery datesof these orders. Thus, the estimated delivery dates and thedue dates can be compared and customer correspondence andproper reactions can be made to achieve an efficient productionto satisfy customers’ demands. Besides, this function canprovide data to customers in regards to the delivery dates oftheir orders.

The fourth step is to calculate the actual releasing quantityof the next day. The main consideration of this step is thestatus of the bottle-neck stations of the production line. If theWIP’s in these stations are too high, the system should releaseless quantity than the planned scheduling quantity in order toprevent increasing the difficulty of shop floor control. Afterthe forth step, the Scheduler, then, schedules the orders withrespected to the releasing quantity determined in Step 4. Theoutputs of the scheduling system are

1) a list of released orders;2) a list of unreleased orders;3) a list of orders that due dates have been revised;4) advice for the setup of machines in each station;5) advice for the demand of workers in each station.

A. Scheduling Process Model

A process model and the related data models for the schedul-ing of IC packaging production are designed for implementingCASS based on the SIS and WIP-inventory approach. Inthis section, the IDEF0 model is selected for determining thedecision process and its control requests. The IDEF0 model isused as a first step toward determining the necessary controls.IDEF0 is a descriptive modeling tool and a powerful functionmodeling technique. By elaborating the descriptive text andits graphical representation of the scheduling system, IDEF0provides an explicit representation of the system functions andprocess flow.

IDEF0 is derived from the structured analysis and de-sign technique (SADT) as both an analysis tool and a com-munication tool in many areas [28]. Its structural analysismethodology provides the ability to present the complexfunctional relationships hierarchically. Each box, referred toas the unit of an IDEF0 model, corresponds to an activity tobe performed. Four types of arrows are associated with a box.They are input, output, control, and mechanism, respectively.A box also indicates the boundary of an activity, and can

TABLE IRELATIONSHIP OF FACTORS OF THEIDEF0 MODEL

AND THE ENTITIES OF THE EXPRESS MODEL

be further broken down into several sub-activities. Thesesub-activities, located at a lower level, must represent thecontent of their superior activity consistently. Related boxesat the same level define a functional network. Connectionsbetween boxes represents flows of control, information or ob-jects used/required/processed between activities. Based on theentire IDEF0 model, one can explicitly observe the decisionprocesses of the scheduling system.

An overview of the scheduling system is shown in Fig. 2.The inputs of this system include the forecast capacity of eachproduct and the received orders. The outputs of this system arethe lists of unreleased orders, released orders, due-date revisedorders, suggestion of machine setup status and the number ofworkers in each station. The inputs, constraints, and outputsof the system are listed in Table I.

Fig. 3 is the detailed exposition of the IDEF0 A-0 diagramfrom Fig. 2. The first functional box represents pre-schedulingof the received orders. The objective of pre-scheduling is toschedule all of the orders received for production planning. Inpre-scheduling stage, the system does not consider the statusof the bottle-neck stations and only computes the expecteddelivery dates of the orders. The department of productionplanning will inform the customers and execute the reactionof the customers. After pre-scheduling, the system schedulesthose orders by the actual released quantity that is calculatedbased on the status of the WIP’s in the bottle-neck stations.


Fig. 2. The IDEF0 A-0 diagram of the scheduling system.

Fig. 3. The IDEF0 A0 diagram of the scheduling system.

Fig. 4 describes the sub-steps broken down from the pre-scheduling function (A1). The first step is to decide the dailyplanning scheduling quantity of the next week and to arrangeall of the received orders by the sequence of their due dates.After obtaining the quantity of the daily scheduling and the

list of arranged orders, the orders are pre-scheduled. Then,the system checks the due dates and the pre-scheduled duedates. If an expected due date is later than its original duedate requested by the customer, the system will output the listof due dates for revising.


Fig. 4. The IDEF0 A1 diagram of the scheduling system.

B. Scheduling Data Schema

Data modeling starts from defining the data requirementsof an application. In this research, data requirements areacquired from the production management department of a realIC packaging plant. The data including quantities of WIP’s,requirements of customers, status of orders, and resourcesare necessary for the system to perform scheduling task.Data models are designed to provide information structureto support the IC packaging scheduling system. EXPRESSlanguage is used to specify the scheduling schema which isorganized into three models: product data model, resource datamodel, and input data model. As mentioned in the previoussection, EXPRESS is an international standard data modelinglanguage, which has an extension called EXPRESS-G forgraphical representation of EXPRESS model.

An EXPRESS schema, called scheduling-system, is definedin this research. The corresponding EXPRESS-G representa-tions for all entities and data types are illustrated in Figs. 5–7.The relationships between the factors of IDEF0 process modeland entities of EXPRESS data models are also summarizedin Table I. Types and entities of the scheduling schema aredescribes as follows.

1) Product Data Model:A “product” entity represents theIC packaging product (Fig. 5). Thename attribute is theproduct’s name. Attributeid is the identification number ofthe product. Attributepriority is the releasing priority formanufacturing the product. Attributeictypeis the product typeof the IC packaging and its value is defined as an extendedtype, ic_type. Attribute pin_count is the amount of IC pincount. Attributelead_frame_nois the ID number of lead frameused in IC packaging. Attributereleased_wip_buffer_dayin-putted by the planner is the quantity of released orders and

is expressed by the quantity of daily capacity. This attributeis used for preventing WIP stocked in the front station ofpackaging processes. Attributeproduction_rate_buffer_daysetby the planner is expressed by daily capacity and is thequantity of buffer for the continuous status of production linepreventing the cost of stand-by time.

2) Resource Data Model:This group of data modelscompose of entities such asstation, machine, worker andthe capacities on stations and machines(shown in Fig. 6).The station entity is defined by five attributes:name, id,owned_machines, average_uph_capacityandowned_workers.The name defines the process name of this station inIC packaging, e.g., die mounting station, wire bondingstation, molding station, etc. Theid defines the identificationnumber of this station. Theowned_machinesdefines acollection set of machines in this station. Theowned_workersdefines also a collection set of workers in this station. Theaverage_uph_capacityis the data of the unit output per hour inthis station, which is provided by the department of industrialengineering.

Thestation_uph_capacityentity defines the capacity of eachstation for a specific product; Attributeproduct_iddefines theidentification number of the product. Attributeuph_capacitydefines the capacity unit per hour of machining the productin the station. Themachine entity defines the facility ofprocessing a specific process. Attributenamedefines the nameof this machine. Attributeid defines its identification number.Attribute suit_product defines a collection of the specificcapacity for machining a product. Attributesetup_product_iddefines the setup status of machine. Attributeneed_worker_nodefines the average number of workers required to operatethe machine, which could be a real number when one workeroperates several machines.


Fig. 5. The product data model of the scheduling system.

The suit_product_capacity entity defines the specificcapacity of machining a product. Attributesuit_product_iddefines the identification number of the product. Attributeuph_capacitydefines the capacity unit per hour of machiningthe product. An instance of the entityworker can operatemachines. This entity has two attributes:name and id foridentification.

3) Input Data Model (Fig. 7):The order entity defines ageneral characteristic of a customer’s order. Its due daterequested by the customer may be or may not be changed(defined in two subtypes).Order consists of basic attributessuch asid, customer_id, product_type, status, quantity, cus-tomer_due_dateand come_on_date. Statusdefines the statusof the order, which may be unreleased, released or finished.Quantity defines the requested quantity of the order.Cus-tomer_due_datedefines the due date asked by a customer.Come_on_datedefines the date that the planner received theorder. Further as the subtype oforder, therevised_orderentityis an order that the due date has been changed. An additionalattribute, revise_to_date, defines the changed due date. Theunrevised_orderentity is an order that the due date is notchanged.

In order to describe customers, thecustomer entityis defined. It includes attributes:name, id and capac-ity_requirement. The capacity_requirementattribute definesthe capacity required by a customer. Further, thecus-tomer_capacity_distributionentity defines the distributedcapacity for a specific product to a customer. Attributeday_capacityis the quantity distributed to a customer.

The forecast_day_capacityentity indicates the day capacityof the production line for a specific product. Attributeon_dateis the date of the forecasted production. Attributeday_capacity

is the forecasted quantity of a product. Thewip entity in-dicated the quantity of WIP in a station on a specific date.Attribute on_dateis the date of the WIP occurred. Attributein_station_idis the identification number of a station where theWIP occurs. Attributeproduct_idis the identification numberof the product type that the WIP belongs to. Attributequantityis the quantity of the WIP. Finally, theschedule_statusentitydefines the daily status of each product on the schedule report.Its attributeon_dateis the date of a released order. Attributeproduct_idis the product type requested by the order. Attributescheduled_quantityis the released quantity of each product onthe date.

IV. COMPUTER-AIDED SCHEDULING SYSTEM

A. System Overview

The goal of developing the computer-aided schedulingsystem is to satisfy the scheduling requirement and ease ofuse by an IC packaging company. One of the objectives of theSTEP-compatible CASS is to let the system has interfaces thatcan communicate information and data from other departmentsor companies. The CASS is written in C and run on aSun SPARC10 workstation. C was chosen for its currentpopularity among professional programmers as well as forits modular approach to system creation by object-orientedextensions. Implementing the system in a UNIX environmentappears to be logical because almost all workstations run underthe UNIX environment.

The CASS consists of six modules, which are tightly con-nected: the input module, the shop floor status analysis module,


Fig. 6. The resource data model of the scheduling system.

the capacity analysis module, the pre-schedule generator, thereleasing analysis module, and the schedule generator. Anoverview of the CASS is described in Fig. 8.

The interface passes commands and parameters to theCASS. The shop floor status analysis module then performscomputing the capacity limitation and releasing limitation bythe data of wip status and schedule history. The capacityanalysis provides the feasible capacity to the pre-schedulegenerator by analyzing the capacity limit and the in-linestatus of the manufacturing system. The pre-schedule generatorretrieves the orders file from the database and schedules allof the received orders by the feasible capacity. The schedulegenerator then uses the releasing quantity to schedule the ordersequence computed by the pre-schedule generator.

B. Implementation Environment

The implementation approach for the CASS is depicted inFig. 9. The software tools used by this research include IDEF0methodology, EXPRESS language, express2ctranslator,C language, ROSE database, ST-ObjectStore databaseadapter, and ObjectStore database. For developing an ICpackaging scheduling system, the first step is to acquire the

knowledge of scheduling and then to construct the schedulingprocess model and data models. The methodology of IDEF0is employed to establish the process model. The EXPRESSlanguage is used to define a scheduling system schema, whichconsists of entities and data types that relate to objects ofCASS.

The object-oriented database, ObjectStore which is anobject-oriented database management system, is used to makeapplication objects persistent. It combines the data query andmanagement capabilities of a traditional database with theflexibility and power of the C language. The C isselected to implement the scheduling decision processes.

The ROSE database is implemented as a class librarythat allows application programs written in different object-oriented programming languages to share data defined by theSTEP standards. The interface between the Cprogram-ming language and the ROSE database is called ROSE.ROSE provides methods for a C program to create,read, write, and manipulate design objects in a ROSE database.The data can be either stored as STEP objects or translatedinto a STEP file. The ROSE system provides a tool, namedthe express2c , to generate the C object classes from


Fig. 7. The input data model of the scheduling system.

the EXPRESS data structure definitions. The express2ctool takes an EXPRESS schema as input to generate theC class definition for each entity (data structure) in theschema. The tool defines C classes by inheritance functionsfrom corresponding ROSE superclasses, which have thefunctionality to manage STEP objects in a C program.

The interface between the ROSE database and the Ob-jectStore database management system is the ST-ObjectStore,which contains the ROSE class library that can store and ma-nipulate STEP data within the ObjectStore database. The ST-ObjectStore applications can be characterized into four groups:

STEP application, STEP/OS translator, OS/STEP translator,and ObjectStore application. In this research, the STEP/OStranslator is used to loads data stored in STEP files into anObjectStore database. A C application program for thescheduling system is developed to complete the tasks of thescheduling functions which can access the scheduling relatedobjects stored in the ObjectStore database.

C. Implementation Procedure

With the environment described above, the process bywhich a scheduling system of IC packaging industry can be


Fig. 8. Overview of CASS.

implemented using STEP enabling technology. The process issummarized as follows.

1) Knowledge acquisition of the IC packaging scheduling:Analyze the information flow of the scheduling system.Identify the information requests of a computer-aidedscheduling system (CASS). Use the process modelingmethodology of the IDEF0 to understand the schedulingprocess.

2) Establishment of the scheduling information model:Model the scheduling system data structures using theEXPRESS information modeling language.

3) Generation of the class library: Generate C classesfor each entity in the EXPRESS schema using theexpress2c tool. These classes will be subtyped assubclasses of ROSE classes. As a result of using theexpress2c , a class definition is generated for eachEXPRESS entity in the data model of scheduling system.

4) Creation of the instances of the resource and ordermodels: Create instances of the C classes generatedby the tool within a ROSE application program.These instances are the application objects which willstore the data of the manufacturing system and receivedorders.

5) Adaptation of the STEP data: Use the step2os translatorof ST-ObjectStore to load data from a STEP file intoan ObjectStore database. The program code of step2ostranslator is a general purpose program.

6) Development of the Computer-Aided Scheduling Sys-tem: Develop the CASS in C for UNIX and run ona Sun SPARC10 workstation.

D. Example

In this example, the scheduling system deals with fivestations and four product types. The four product types are:100Q, 28J, 28K, and 40P. The four product types and the dataof each product type is described in Table II. As shown inTable III, the five stations in sequence are

1) mounting;2) bonding;3) molding;4) marking;5) trimming/forming.

The first step of the CASS is to retrieve the planningcapacity of each product and calculate the daily scheduling

Fig. 9. The implementation procedure and environment of the CASS.

TABLE IIEXAMPLE PRODUCT DEFINITION

TABLE IIIEXAMPLE STATION DEFINITION

quantity of the next week. The system refers to the forecastcapacity in the eighth column of Table II for the schedulingof the next week. The CASS checks whether the capacity canbe accepted by the production system.

The shop floor status analysis module derives the status ofthe production system, shown in Table IV, using the schedulereport and the WIP report. Then, the CASS calculates the dailyscheduling quantity for the next week as shown in Table V.


TABLE IVSTATUS OF THE PRODUCTION LINE CALCULATED

FROM WIP AND SCHEDULE REPORT

TABLE VDAILY SCHEDULING QUANTITY

TABLE VIPRE-SCHEDULING RESULTS

TABLE VIITHE RELEASED QUANTITY OF TODAY

Hence, the capacity analysis module accomplishes the firstprocedure of the scheduling task.

The second step is the pre-schedule generator sequencesall of the orders based on their due dates. After the capacityanalysis module calculating the daily scheduling quantity andarranging all of the orders, the Pre-schedule Generator pre-schedules all of the orders by the daily scheduling quantity.The output of Pre-schedule Generator is shown in Table VI.The next step is the Schedule Generator to fine-tune the actualreleasing quantity of the next day. The main considerationof this step is the status of the bottleneck stations of theproduction line. The result is shown in Table VII. In thefinal step, the Schedule Generator schedules the orders withrespecting to the releasing quantity listed in Table VII, andoutputs the released orders of today as shown in Table VIII.

V. CONCLUSION

Most researches in the semiconductor manufacturing sched-uling focus on the front-end processes. The development

TABLE VIIITHE RELEASED ORDERS OF TODAY

of a scheduling system for the IC packaging industry isessential for improving efficiency of the back-end processesin semiconductor production. This research adopts the conceptand method of STEP enabling technology to implement the ICpackaging scheduling application. The effort aims to achieveintegration of engineering applications by standardizing thedesign and the use of product data.

In this research, a prototype computer-aided schedulingsystem (CASS) for IC packaging industry is proposed. Allthe data used in the prototype CASS is collected from theIC packaging industry. The scheduling system is designed forshort interval scheduling of IC packaging manufacturing. Thisresearch uses IDEF0 to model the IC packaging schedulingprocess, and EXPRESS language to define the data models.The prototype IC packaging scheduling system is implementedin an integrated environment with object-oriented language(C ) and database (ObjectStore). The ST-Developer is usedas the kernel to interface the application language, database,and EXPRESS data model and has the capacity to output theinstanced objects as STEP file format. The architecture of thisintegrated implementation environment is not only effectivefor scheduling task but also useful in general product design,analysis, and manufacturing planning. Using and defining ap-plication information in a standard way is necessary to supportconcurrent engineering practice in an enterprise. The integratedenvironment of the CASS can be applied in the standardizationfor product design, product analysis, and process planning.

The contribution of the CASS for IC packaging productionplanning is that the scheduling time can be reduced, becausethe CASS automatically assists the production planner toschedule all of the orders considering the scheduling con-straints and inputs. Particularly, the CASS is suitable forre-schedule when unexpected events occurred on the shopfloor.It can quickly provide a re-schedule to react the conditionsand assist the manufacturing department in controlling theshopfloor.

The EXPRESS schema developed in this research onlyconsiders data management for scheduling. To fully captureall information related to process capacities and involvedresources within an enterprise, the resource model should beextended to integrate with other engineering applications in amanufacturing system. There is still much work to be donein the information modeling of manufacturing resources. It isa challenge to model variety of information and functions ofan enterprise, and to achieve full integration for all activitieswithin a product life cycle. An issue can be addressed in the


future work is to integrate the CASS with other computer-aided systems for an enterprise as the basis of computerintegrated manufacturing (CIM).

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Thu-Hua Liu received the M.S. degree inmechanical engineering from Stevens Institute ofTechnology, Hoboken, NJ, in June 1983 and thePh.D. degree in industrial engineering from theUniversity of Iowa, Iowa City, in 1992.

He is an Associate Professor and Chairman ofthe Department of Industrial Design, Chang GungUniversity, Tao-Yuan, Taiwan, R.O.C. His researchinterests include product data engineering andstandardization, STEP-based application, object-oriented system integration, and assemblability

evaluation.

Amy J. C. Trappey, for a photograph and biography, see this issue, p. 229.

Fu-Wei Chan received the M.S. degree in industrial engineering fromNational Tsing Hua University, Hsinchu, Taiwan, R.O.C.

He is a Production Engineer at Macronix International Co., Ltd., HsinchuScience-Based Industrial Park, Taiwan. His interests are in the area ofcomputer aided scheduling system for IC packaging production.

A scheduling system for IC packaging industry using STEP enabling technology

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