PROCESS INFOR-MATION
The concept of a process is fundarnental in the representation of socio-economic resource systems. I t has its theoretical roots in activity analysis (Koopmans, 1951) and has been f u r t h e r elaborated by Georgescu-Roegen (1970).
In recent years, problems of resource scarcity and environmental degradation have led t o the extension of economic systems t o include natural resources, externalities and socio-demographic factors. Energy analysis, environmental impact analysis, and technology assessment have become significant new fields for applied research. The feature common to these areas of interest is t h e focus o n t h e processes t h a t transforni resources and energy into t h e goods or services t h a t m e e t h u m a n needs.
Over t h e last 25 years, t h e r e have been two relatively independent lines of development of applied process models in economics: input- output models a t t h e macro-economic level (Leontieff, 1951;
Matuszewski, 1972; a n d Gigantes, 1970), and, sector specific process models as for instance described in Hudson and Jorgenson (1978), Russell and Spofford (1972), Russell (1973), Kydes and Rabinowitz (1981), Pilati a n d Sparrow (1980) a n d Carasso e t al. (1975). The importance of process models has also been recognized in the field of ecology (Clark and Hol- ling, 1979).
Process models t e n d t o be information-rich. Limitation in t h e avai- lability of process information imposed by t h e cost of obtaining s u c h information has r e s t r i c t e d t h e development of process models (Hudson a n d Jorgenson, 1979).
Input-output process information is readily available in m o s t coun- t r i e s a s i t is compiled a n d published by national statistical offices, how- ever, for m o s t applications, t h e input-output representation of a process is not adequate for t h e following reasons: the process boundaries a r e not well defined; flows a r e m e a s u r e d in c u r r e n c y units; t h e r e a r e no stocks;
t h e information is retrospective i n t h e s e n s e t h a t t h e descriptions a r e derived from m e a s u r e m e n t s of p a s t
-
usually 3 to 5 y e a r s-
flows;processes a r e represented a t a relatively high aggregate level, a s a result of t h e use of c u r r e n c y units; t h e degree of aggregation a n d t h e u s e of c u r r e n c y u n i t s m a k e t h e process descriptions time a n d nation specific in t h a t e a c h description r e p r e s e n t s t h e specific mix of processes a t t h a t t i m e a n d place; finally t h e relationships between i n p u t flows a n d t h e out- put flow for e a c h process a r e l i n e a r a n d proportional.
R o c e s s information compiled for sector specific models is normally compiled b y the model developers. In fact, t h e compilation of process d a t a usually requires t h e preponderance of r e s e a r c h funds in t h e development of process models. I n f o n a t i o n from this source is usually richer t h a n input-output d a t a in t h a t i t is measured inphysical quantity units; i t is m u c h less aggregated a n d process boundaries b e t t e r defined.
However, process d a t a collected for s e c t o r specific process models a r e not readily accessible because t h e y a r e dispersed over a large n u m b e r of r e s e a r c h institutions, none of which has a specific m a n d a t e for
information dissemination. Furthermore, process descriptions compiled for sector specific models are often incomplete -- for example process descriptions compiled for energy modeling may not include non-energy flows. Also t h e information is in t h e specific form required by t h e mathematical s t r u c t u r e of t h e model a n d its computer system. For example, t h e process descriptions take t h e form of constraints in an optimization framework.
Both t h e WELMM project of IIASA and t h e Process Encyclopedia pro- ject of Statistics Canada represent a t t e m p t s t o compile data bases of pro- cess information. Initially these data bases were intended to support particular modeling applications. h both c a s e s i t became clear that pro- cess descriptions could be compiled in such a w a y that they could support a v a r i e t y of different modeling applications. Indeed processes can be defined such t h a t they a r e neither site-, nor plant- nor nation- specific
-
a t least for a large number of processes. Equally i t is possible t o link or
"map" two systems together, which was a t t e m p t e d between the two sys- t e m s described hereafter (see Figure A-4-1 and Griibler e t al, 1982).
A4-1-1:THE FACILITY DATA BASE OF THE WELMM APPROACH
In order t o assess the natural resource requirements of resource development strategies (in particular energy strategies) an analytical approach called WELMM was developed a t IIASA (Grenon and Lapillonne, 1976). The WELMM approach involves an assessment of the requirements and t h e availability of Water, h e r g y , Land, Materials and Manpower resources. For quantitative analysis, t h e
WELMM
approach is based on computerized data bases of primary resource availability a t t h e global,I
..
High level representation of PE -,FDB
mapping.national or regional level (Medow, 1983; Grenon and Medow, 1983; Mer- zeau, 1980), and on data bases of resource requirements for industrial processes deployed in processing primary (energy) resources t o t h e com- modities required by t h e final consumer (see Figure A-4-2). At each of t h e transformation steps of such a resource processing system, corresponding industrial processes can be defined. Within t h e Facility Data Base (FDB) (Grubler and Cellerier, 1983), t h e boundaries of t h e pro- cess analyzed a r e drawn in such a way t h a t a process corresponds t o an industrial unit or facility. The technological characteristics of any par- ticular facility a r e independent from t h e i r location; in addition t h e r e is an increasing t r e n d towards standard size classes, particularly for energy facilities (e.g., pressurized water reactors of 1000 o r 1300 MWe, crude oil tankers of 250000 or 300000 DWT, etc.). Both factors men- tioned above make WELMM-type analyses (i.e., a t a "typical" industrial facility level) easier for a variety of applications including comparisons of alternative technologies for t h e production of specific products o r ser- vices (Grubler, 1980; Merzeau, Grenon and Grubler, 1981; and Katsonis and Gourmelon, 1983), or for t h e comparison of whole resource process- ing systems (Resources Group, IIASA, 1979 and Griibler, 1984). However, t h e process boundary defined for t h e FDB is flexible
-
a t a conceptual level and from t h e point of view of t h e actual data base s t r u c t u r e . Aggre- gation and disaggregation of processes stored in t h eFDB
have been tested and have proved feasible (Kopytowski e t al., 1981).Also i t should be noted t h a t t h e concept of a "typical" facility with respect to technology and size cannot be applied to primary resource extraction processes because t h e individual deposit characteristics
d e t e r m i n e t h e choice of t h e appropriate technology as well a s t h e proper r e s o u r c e flows for t h e construction a n d operation of a mine. The FDB h a s t h e r e f o r e been complemented by a s u b s t r u c t u r e on coal mines, tak- ing t h e individual deposit c h a r a c t e r i s t i c s into account. The d a t a of t h e Coal Mines Data Base (CMDB) is f u r t h e r analyzed by statistical analysis techniques t o obtain relational d a t a on t h e influence of deposit p a r a m e - t e r s on technology choice a n d WELMM r e s o u r c e requirements ( ~ s t a k h o v e t al., 1983).
Another c h a r a c t e r i s t i c of t h e F'DB is t h a t it covers both the a c t u a l t r a n s f o r m a t i o n p r o c e s s , as w e l i as the c o n s t r u c t i o n process of t h e p l a n t (the f u n d ) , in which t h e transformation takes place. Within t h e FDB t h e resource-Flows a r e accounted for e i t h e r a s a t o t a l of the c o n s t r u c t i o n period o r per y e a r of full s t r e a m operation. The r e s o u r c e flows a c c o u n t e d for a r e direct r e s o u r c e r e q u i r e m e n t s , i.e. t h e r e s o u r c e flows c o n s u m e d on-site for t h e construction and operation of a facility (con- c r e t e , s t r u c t u r a l steel, water, chemicals, etc.) and those r e s o u r c e s (e.g., metals) embodied in t h e capital goods of a facility which a r e physically on site.
After t h e collection of raw d a t a (through literature, existing d a t a bases o r questionnaires) t h e d a t a is analyzed before computerization.
The information on a particular process in t h e FDB is paradigmatic i n t h e s e n s e t h a t t h e d a t a s t o r e d a r e " h a r d data. The data analysis a n d judgement is documented within t h e FDB which contains qualitative a n d bibliographical information in addition t o numerical information.
WELMM PROCESS ANALYSIS
JG:G
Primary Input***
* * b e .
Energy Direct
4 I- - +
IndirectI
t I
ManpowerL--Capital Goods
V N nOutput
Physical Losses & Wanes
Figure A-4-2.
WELMM
process analysis.The data in t h e FDB is divided into four blocks: process identifica- tion (name, location, capacity, etc., including two t e x t files with informa- tion on t h e particular facility as well as on t h e process(es) i t deploys), process characterization (list of primary and secondary inputs and n e t outputs), WELMM requirements for construction and, finally, WELMM requirements for operation. In t h e last two, data is accompanied by a quality indicator (ranging from one t o five and indicating possible ranges of uncertainty) and a footnote (giving details about t h e origin of t h e data, conversion factors employed and/or alternative data estimates).
For t h e CMDB t h e d a t a organization is similar, however t h e particular mine and its deposit is described in more detail in 14 blocks followed by the WELMM requirements for construction and operation (stored as specific values t o facilitate further analysis and generation of relational information) a n d a t e x t footnote.
All data are s t o r e d in a relational data base management system called INGRES (developed a t t h e University of Berkeley) (Held e t al., and Woodfill e t al., 19?9), which operates on top of t h e UNIX system on a PDP
11/70. Additional interactive programs developed within the WELMM Pro- ject for data e n t r y a n d retrieval, statistical analysis a n d linking t o o t h e r data bases on primary resource availability, have been implemented.
A4-1-2:THE PROCESS ENCYCLOPEDIA PROJECT OF STATISTICS CANADA The Structural Analysis Division of Statistics Canada i s a research group concerned with t h e development and operation of 'structural' economic models of t h e Canadian economy. The first models were com- parative static input-output models which were extended in a variety of ways t o include energy flows in physical units, employment, interactions along provinces, and prices (Structural Analysis Division, 1980a). In t h e last five or six years, t h e focus of t h e development work shifted to time structured socio-economic-resource modeling.
From this experience i t became clear t h a t input-output representa- tions of 'production' processes were inadequate for the reasons outlined above. As a result i t was decided to establish a project to determine the feasibility of compiling a data base of industrial process descriptions;
this data base became known as t h e Process Encyclopedia.
In t h e methodology of the Process Encyclopedia, a process is described by means of three basic sets of information:
Definitional Enfornation, which consists of a process name, t h e names of the flows t h a t cross t h e process boundaries, and t h e names of t h e transformation nodes and funds within the boundaries. This defini- tional information is in fact a directed graph which in the language of the Process Encyclopedia is called topography.
Relational h f o r m a t i o n , which describes the form of t h e relation- ships among t h e flows of a process. This relational information defines t h e parameters of t h e functional forms of t h e process model, or as it is called in the Process Encyclopedia: t h e generic model.
Q u a n t i t a t i v e I n f o r m a t i o n , which is simply t h e values of the parame- ters defined by the generic model associated with t h e topography of the process.
There can be more t h a n one generic model associated with each topography and in t u r n t h e r e can be more than one s e t of parameter values associated with each generic model.
?Re e z p l i c i t r e c o g n i t i o n of r e l a t i o n a l i n f o n a t i o n o r g e n e r i c m o d e l s p e r m i t s the r e p r e s e n t a t i o n of n o n - l i n e a r r e l a t i o n s h i p s b e t w e e n input f l o w s a n d o u t p u t f l o w s , t h e d e f i n i t i o n of control v a r i a b l e s , a n d the i n t r o -
d u c t i o n o f t i m e l a g s b e t w e e n input @ o u s a n d o u t p u t f l o w s .
The use of definitional information permits the representation of structure within a process. Funds or stocks can be distinguished from transformation nodes
--
t h u s allowing for dynamic modeling applications.In addition to t h e t h r e e basic sets of information, the Process Ency- clopedia contains indexing information in order to access the data base and also 'observations' of processes. 'Observations' are measured values of the input and output flows. A s e t of observations is associated with a topography which defines t h e flows. Parametric information may be obtained through t h e analysis of observations. Provision is also made for including bibliographic information on data sources and quality.
The Process Encyclopedia is a tool for refining process descriptions as well a s a data base of 'good' process descriptions. Raw data in the state in which it has been found can be e n t e r e d i n t o the Process Encyclo- pedia without transformation. Such data may be incomplete and inaccu- rate in the sense t h a t it h a s not been subject to mass a n d energy bal-
a n c e s o r o t h e r filter edits. This raw d a t a can be analyzed a n d refined within t h e Process Encyclopedia a n d t h e resulting 'good' o r paradigm process c a n be saved in t h e d a t a base. The Process Encyclopedia has b e e n extensively documented ( S t r u c t u r a l Analysis Division, 198Db).
A4-1-3: CONCLUSIONS ON PROCESS INFORMATION SYSTEMS
Process descriptions, which encompass definitional, relational, a n d quantitative information a r e a n appropriate s e t of building blocks from which t o build process models ( w h i c h c a n be o v e r l a i d b y b e h a v i o r a l m o d e l s ) . Process u n i t s c a n be defined a n d quantified in s u c h a way t h a t t h e y a r e n e i t h e r site- nor nation-specific.
Process descriptions t h a t a r e complete in t h e sense t h a t t h e y encompass all input a n d o u t p u t flows including those associated with stocks c a n serve a wide variety of modeling applications. m e m a t h e m a t - i c a l f o r m of t h e d e s c r i p t i o n of e a c h p r o c e s s s h o u l d b e ' n a t u r a l ' a n d i n d e p e n d e n t of t h e m a t h e m a t i c a l f o r m of t h e modeL(s) which m a y use t h e process description. The process descriptions can be transformed by t h e model builder a s required.
Process information is a m o r e detailed level of information t o sup- port modeling activities t h a n a n y o t h e r type of information (e.g., input- o u t p u t tables). I f t h e p r o c e s s i n f o r m a t i o n s y s t e m .is a d e q u a t e l y d e s i g n e d i t is m o d e l - (or a p p l i c a t i o n - ) i n d e p e n d e n t . This in t u r n implies t h a t t h e
u s e r of process information has t o g e n e r a t e his own "paradigmatic" pro- c e s s d a t a o u t of t h e process information system. The process informa- tion system therefore has t o support this "clean" d a t a generation with appropriate tools and/or should store flagged "hard" data, which h a s
been analyzed already for a c e r t a i n field of application (e.g., t h e
WELMM
Facility Data Base data).
Process information i s n o t necessarily c o u n t r y or site specific if col- lected a t the appropriate level (e.g., t h e engineering level). Engineering information of this type a s well a s t h e u s e of physical indicators r e s u l t in d a t a validity over long periods (unlike) economic d a t a or input-output (1-0) tables. Also within t h e concept of process analysis. t h e dynamics of a given s y s t e m (e.g., introduction of new technologies, changing economic or resources intensiveness of a particular process in t h e long- t e r m c a n be dealt with relatively easily (again unlike 1-0 coefficients).
Process d a t a is information-rich, i.e., t h e building of process infor- mation systems is a data-intensive, long-term activity t h a t requires con- tinuity. Because process information has long-term validity i t is possible t o build u p process information systems (provided t h e y a r e carefully a n d flexibly designed) over long periods, s t a r t i n g first with specific application-oriented process information a n d enlarging t h e s y s t e m l a t e r on until sufficient information becomes available for t h e process infor- mation s y s t e m t o be model
--
or application--
non-specific. This goal c a n only be achieved if t h e information s y s t e m is build u p through a n inter- disciplinary a n d international effort. Because process information is not country- or site-specific, problems should not o c c u r i n t h e exchange of process information on t h e engineering level. However, because of t h e long-term n a t u r e of t h e exercise of process information collection, t h e information s y s t e m should be hosted within an environment assuring continuity, a n d adequate ( c o m p u t e r a n d manpower) resources t o support a c e r t a i n level of p e r m a n e n t effort. This environment would best beprovided by a governmental statistical office or t h e like (i.e. t h e CSI).
Once such a process information d a t a base is developed and built up, i t can easily be enriched and enlarged whenever it is accessed for specific applications which in r e t u r n will generate additional information t o be included into t h e system. Again in order t o promote this access or straight link to other process information systems i t is necessary t o ensure a certain minimum, p e r m a n e n t effort in process information sys- tems construction.
A4-2: PROCESS DATA BASE TOOLS: EXAMPLES
FDR
PROCESS TOPOGRAPHlES, PROCESS MODEL DOCUMENTATION LANGUAGE. PROCESS PARADIGMSAND OTHER PROPOSED EDSS TOOIS
The process topography graphical representation language, we have already discussed in Chapter 4 of this paper. Figures A-4-3 and A-4-4 illustrate t h e application of this representation language in representing a facility of t h e
WELMM
Facility Data Base in general and an example of a chemical transformation process s t o r e d in the Process Encyclopedia data base. Further examples of process topographies can be found in t h e process paradigm examples presented in Figures A-4-6 and A-4-7 based on the case study (Katsonis a n d Gourmelon, 1983) which we used already to illustrate t h e decision cycle documentation language SADT in Chapter 3 and Appendix 3. Note here t h a t to-date the topography representation language software is o n l y capable of displaying d e f i n i t i o n a l information on a particular process (i.e., in t h e form of its topography). In a f u r t h e r step t h e same software should be adopted to also present numerical data on t h e flows of t h e process, equally in a graphical summary form like t h e process topography diagram.\
Related t o the process model, Figure A-4-5 displays a Process Model diagram based on t h e s t r u c t u r e d model documentation language developed a t Statistics Canada. Other examples c a n be Found in t h e pro- cess paradigm presented in Figures A-4-6 and A-4-7. The concepts and graphical conventions underlying t h e process model documentation language is further elaborated in t h e following section A4-3 (taken from Mclnnis and Page, 1979).
PUOCESS DlCICciRM EDC VIR VRPOR PhRSE ETHYLENE ChLOR/OXYCHLOR1N4TION TOP0 I 128 SECTION 2 gp 5 2.5 MN QND REFGIRED 3.4 OLO rrcO USLO CaP 11% 2.6 ON hlfr 3.3 OFfHlFT CWIICL
~d~)r:
LAOOUR 6.a o varFigure A-4-5. A process model diagram from t h e Process Encyclopedia
old r&uwa
To Ptm c 'an
Rgure A-4-6. Example for proposed process description in EDSS: pro- c e s s topography for solar energy-electricity conversion with photocells
P r o c e r r Topography: P h o t o c e l l
Code Name O r i g i n
I n t e r n a l f l o v s
--l.ll
m mM r
F u r s l ~ o o r
Ola and u w L b u s
3
Old kmnomj i r r r r v 3
€5 E- LII
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Elrcrr~cnv for tonu- or St-
-
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W m
lMmm F d )
-
V
~ . r w . a u u OW k l r r r ~ a r ~
Figure A-4-6 (5). Example for proposed process description in EDSS: pro- c e s s topography described by process model (solar energy-electricity with photocells)
P r o c e s s M o d e l 1
7 - E g E a S + b ( k c a l ) E3 + E = E 2
5
E4 + E 6 + E 2 = E l E3 = P l P 2 P 3 E 2 = E l P 1 P 2
E3 = S El (x. Yr t ) P1 P 2 P 3
E2 = El P i P 2 E3 = P 1 P 2 P 3
4 = ( 1
-
p 2 ) P1 E l E5 = ( 1-
p3) P1 P 2 El E6 = ( 1-
p l ) E lw i t h
E l = S E l (x, Y. t )
Figure A-4-6 (7). Example for proposed process description in
EDSS:
pro- cess model d a t a base for photocells (part 1)P r o c e s s Model 2 Equations o f Model 1
and :
M7
-
Mg = S ( c + d & ) + e &PF = f (kg)
MP3 = g + hS manhours L1 =
is
i f S > 13.65 m 2= So
= j i f S < 13.65 m2 = So MP3 = MP1
-
MP2MP4
-
MP5 = MP6 + MP7 + MP8L1 = L2 = L3
Figure A-4-6 (8). Example for proposed process description in EDSS: pro- cess model data base for photocells (part 2)
P r o c e s s Model D e s c r i p t i o n
-
163-
~.*rMmuiJ Old
lnrrr Mlr mvJd-
( M o t = F d r l
-
Lopr A A md OauMmriJt Rhm WOld nd UUd
Old F m l i t v
or Oimibutton
w m r
Wanr
En- E n m
(Motor LOQI
F u l l
v
N.rr MmwlY Old m*
T2 S mO l r h r l r
Figure A-4-7. Example for proposed process description in EDSS : pro- cess topography for energy storage with batteries
P r o c e s s Topography B a t t e r i e s
O u t p u t f l o w s
I n t e r n a l flows