{"title":"Editorial note","authors":"Aaron Rose (Editor)","doi":"10.1016/0377-841X(79)90001-9","DOIUrl":"https://doi.org/10.1016/0377-841X(79)90001-9","url":null,"abstract":"","PeriodicalId":100475,"journal":{"name":"Engineering and Process Economics","volume":"4 4","pages":"Pages 433-434"},"PeriodicalIF":0.0,"publicationDate":"1979-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/0377-841X(79)90001-9","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136817952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Measurement of technology progress and capital cost for nuclear, coal-fired, and gas-fired power plants using the learning curve","authors":"Phillip F. Ostwald, John B. Reisdorf","doi":"10.1016/0377-841X(79)90002-0","DOIUrl":"10.1016/0377-841X(79)90002-0","url":null,"abstract":"<div><p>This paper treats the problem of measuring aggregate technology progress and capital cost of gas-fired, coal-fired, and nuclear power plants using the classical learning curve. Regression analysis on disclosed information demonstrates the strength of the technique. Composite learning performance for gas-fired power plants ranges between 85.0% and 88.8% and for coal between 91.7% and 92.8% for the plateau region of the United States. Composite learning performance for nuclear power plants ranges between 78.3% and 81.3% for the United States. Changes in the learning progress for coal-fired and nuclear power plants are revealed beginning in 1973. Technique and interpretation of the data are provided. Adoption of the method as an aggregate predictor of technology progress and cost is encouraged.</p></div>","PeriodicalId":100475,"journal":{"name":"Engineering and Process Economics","volume":"4 4","pages":"Pages 435-454"},"PeriodicalIF":0.0,"publicationDate":"1979-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/0377-841X(79)90002-0","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78585431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Modelling capital expenditure","authors":"R.F. de la Mare","doi":"10.1016/0377-841X(79)90004-4","DOIUrl":"10.1016/0377-841X(79)90004-4","url":null,"abstract":"<div><p>This paper examines the errors in capital appraisal which result from the conventional treatment of capital expenditure on an end-of-year basis. A novel capital expenditure model is developed and validated. This model will permit the realistic, easy and cheap modelling of capital expenditure programmes and the proper representation of such expenditures in capital appraisal calculations. In addition, it is thought that the model could be of joint use to the Project Manager and Financial Controller in executing better project control.</p></div>","PeriodicalId":100475,"journal":{"name":"Engineering and Process Economics","volume":"4 4","pages":"Pages 467-477"},"PeriodicalIF":0.0,"publicationDate":"1979-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/0377-841X(79)90004-4","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88304555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Diary of events","authors":"","doi":"10.1016/0377-841X(79)90005-6","DOIUrl":"https://doi.org/10.1016/0377-841X(79)90005-6","url":null,"abstract":"","PeriodicalId":100475,"journal":{"name":"Engineering and Process Economics","volume":"4 4","pages":"Pages 479-480"},"PeriodicalIF":0.0,"publicationDate":"1979-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/0377-841X(79)90005-6","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136817953","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Models for present-worth analysis of selected industrial cash flow patterns","authors":"Brian Almond, Ronald S. Remer","doi":"10.1016/0377-841X(79)90003-2","DOIUrl":"10.1016/0377-841X(79)90003-2","url":null,"abstract":"<div><p>The present worth derivations of six continuous cash flow models are presented for common industrial economic applications. An approximation method is provided for calculating the present worth of cash flows for nonintegrable models. Two special limiting cases of particular use in engineering screening analyses are given for all six models. A practical example is presented for each of the cash flow models. These examples are drawn from the author's industrial and governmental experience and include the following applications: (1) manpower reductions because of computerized process control, (2) construction-period cash flows, (3) sales revenue forecasts for new polymers, and (4) cash flows for a pollution-abatement facility.</p></div>","PeriodicalId":100475,"journal":{"name":"Engineering and Process Economics","volume":"4 4","pages":"Pages 455-466"},"PeriodicalIF":0.0,"publicationDate":"1979-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/0377-841X(79)90003-2","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77878681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Production program planning in the metal products industry using linear optimization","authors":"Ulrich Berr","doi":"10.1016/0377-841X(79)90025-1","DOIUrl":"10.1016/0377-841X(79)90025-1","url":null,"abstract":"<div><p>A classical example of the Linear Optimization (Linear Programming, LP) is the Planning of Production Program (PPP). But there are unfavourable conditions in the metal products industry: The products are composed of a lot of parts and groups which exist very often in various combinations and/or which can form cross-linked assemblies of prefabricated machine parts. Most of the matrices have approx. 50 % non-zero elements and rectangular shape with a large number of columns. The feasible basic solutions are to be increased by organizational and computing means. To decrease the number of variables the products are comprehended to groups of products.</p></div>","PeriodicalId":100475,"journal":{"name":"Engineering and Process Economics","volume":"4 2","pages":"Pages 99-110"},"PeriodicalIF":0.0,"publicationDate":"1979-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/0377-841X(79)90025-1","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80090273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Paper industry productivity — The real-time control of fibre weight","authors":"Robert S. Collins","doi":"10.1016/0377-841X(79)90028-7","DOIUrl":"10.1016/0377-841X(79)90028-7","url":null,"abstract":"<div><p>In the paper industry productivity, as measured in terms of the utilization of raw materials, energy and machine capacity, is critically dependent upon fibre weight control.</p><p>Recent developments in both micro and mini-computer technologies make the implementation of computationally complex algorithms for the real-time control of the paper-making process a feasible proposition. Two control algorithms, one of which allows for real-time optimal control, are described, and the results obtained from a simulation study of both are reported.</p></div>","PeriodicalId":100475,"journal":{"name":"Engineering and Process Economics","volume":"4 2","pages":"Pages 129-140"},"PeriodicalIF":0.0,"publicationDate":"1979-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/0377-841X(79)90028-7","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91070664","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An investment and financial planning system for the road transport industry","authors":"Michel Klein, Alain Manteau, J. Raphael","doi":"10.1016/0377-841X(79)90033-0","DOIUrl":"10.1016/0377-841X(79)90033-0","url":null,"abstract":"<div><p>A Decision Support System was designed to help road transport companies achieve Financial Diagnosis and Financial planning.</p><p>The functional requirements of such a system are presented as well as an analysis of the decision process of users.</p><p>The system is briefly described and some of the early results of its use given.</p></div>","PeriodicalId":100475,"journal":{"name":"Engineering and Process Economics","volume":"4 2","pages":"Pages 193-210"},"PeriodicalIF":0.0,"publicationDate":"1979-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/0377-841X(79)90033-0","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86711374","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Operational research in practice","authors":"H.J.M. Lombaers","doi":"10.1016/0377-841X(79)90036-6","DOIUrl":"10.1016/0377-841X(79)90036-6","url":null,"abstract":"<div><p>Operational research is the building and use of mathematical models to assist decision-taking. Literature of this subject concentrates on the models and the mathematical procedures to solve them. At least as important, however, are activities preceeding and following the mathematical part, such as problem definition, data gathering, creating alternatives, testing the model, presenting results of the model and controlling the implementation. These practical aspects can be learned using cases. This will be illustrated.</p></div>","PeriodicalId":100475,"journal":{"name":"Engineering and Process Economics","volume":"4 2","pages":"Pages 245-248"},"PeriodicalIF":0.0,"publicationDate":"1979-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/0377-841X(79)90036-6","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91526035","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Interactive methods for the study and operation of material requirements planning (MRP)","authors":"John G. Carlson Ph.D.","doi":"10.1016/0377-841X(79)90027-5","DOIUrl":"10.1016/0377-841X(79)90027-5","url":null,"abstract":"<div><p>An operational, interactive MRP system can be used for the study of the impact of suboptimizing models on the economics of production as well as pretesting the effects of the inevitable changes caused by engineering revisions, vendor delays, production interruptions or customer demand and schedule changes. Both optimizing techniques and common hueristics applied to a modest Master Production Schedule can be treated with the simulation model incorporated in the MRP program. Since the advent of computer based MRP systems, managers have had the visibility to anticipate shortages through the planned availability displays of MRP exception reports. However, the economics of a decision are difficult to test in a real environment but with an MRP simulation model, the alternatives of expediting, de-expediting, lot size changes and Master Schedule changes can be costed particularly with respect to inventory investment.</p></div>","PeriodicalId":100475,"journal":{"name":"Engineering and Process Economics","volume":"4 2","pages":"Pages 117-127"},"PeriodicalIF":0.0,"publicationDate":"1979-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/0377-841X(79)90027-5","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85106068","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}