{"title":"Review evolution of cellular manufacturing system’s approaches: Human resource planning method","authors":"Aidin Delgoshaei, Armin Delgoshaei, Ahad Ali","doi":"10.5267/j.jpm.2018.7.001","DOIUrl":"https://doi.org/10.5267/j.jpm.2018.7.001","url":null,"abstract":"32 Fig. 1. A Flow Diagram of worker assignment in a Cellular Manufacturing System 1.1 Optimum Number of Workers Perhaps, finding the optimal number of workers is the main idea of investigating HRM in CMS. To determine optimal number of operators and part assignment, Park and Lee (1995) developed a 2-stage model while in first stage, a Taguchi method was used to determine system performance which was then used as objective function of assigning model. The idea of maximizing saving costs between operation and outsourcing costs was investigated by Heady (1997). But their model did not investigate operator level, training, hiring and firing costs. Norman et al. (2002) proposed a model to assign workers in manufacturing cells in order to maximize the system profit. Ertay and Ruan (2005) developed the idea of determining number of operators for maximizing number of outputs. For this purpose, using weighted input data, a data envelopment analysis (DEA) was applied. But in the proposed model, the same skill for all operators and machines was considered. 1.2 Promoting and Assigning Skilled Workers Since in real industries, operator’s skill are not same, so their outputs will not be the same. The idea of considering operator levels was investigated by Suer and Cedeño (1996). For this purpose, a mixed integer programming method was used to generate alternative operator levels and then another integer programming is employed to find the optimal operator assignments to the cells. Askin and Huang (1997) used integer programming for assigning workers to cells in order to determine a training program for employees. Aryanezhad et al. (2009) considered 3 skill levels for workers, which can be promoted through the planning horizon by training. Then a multi-period scheduling model was developed for simultaneous cell forming and worker assignning. Jannes et al. (2005) focused on assiginings workers to team works with the aims of minimizing training and assigning costs as well as maximizing labor flexibility. In the same year, Fitzpatrick and Askin (2005) argued that elemens of a good team formation is not limited to personnal skills and characteristics but technological and human interactions. Hence, by using pre-determined skill level measures, they tried to select workers and assign them to appropriate teams in cells to maximize team performance. Cesaní and Steudel (2005) focused on some factors on deployment of labors. Then, they focused on work sharing, work balancing and leveling the operator assignments (in presence of bottleneck operations). To prevent overloading and over-assigning of operators, Satoglu and Suresh (2009) used goal programming in a mathematical model where the objectives were minimizing over assignment of workers, cross training, hiring and firing costs. 1.3 Cross-trained workers Note that cross-trained workers are refered to those workers that are trained to perofrm more than one task. Determinining best sets of crosstraining workers can impr","PeriodicalId":42333,"journal":{"name":"Journal of Project Management","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.5267/j.jpm.2018.7.001","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70780298","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":"A CRITIC-TOPSIS framework for hybrid renewable energy systems evaluation under techno-economic requirements","authors":"M. O. Babatunde, D. Ighravwe","doi":"10.5267/J.JPM.2018.12.001","DOIUrl":"https://doi.org/10.5267/J.JPM.2018.12.001","url":null,"abstract":"","PeriodicalId":42333,"journal":{"name":"Journal of Project Management","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.5267/J.JPM.2018.12.001","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70780371","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":"A simheuristic for bi-objective stochastic permutation flow shop scheduling problem","authors":"E. M. González-Neira, J. Montoya-Torres","doi":"10.5267/J.JPM.2019.1.003","DOIUrl":"https://doi.org/10.5267/J.JPM.2019.1.003","url":null,"abstract":"","PeriodicalId":42333,"journal":{"name":"Journal of Project Management","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.5267/J.JPM.2019.1.003","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70780528","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":"Assessing public sector road construction projects’ critical success factors in a developing economy: Definitive stakeholders’ perspective","authors":"I. S. Damoah, Anthony Ayakwah, Paul Twum","doi":"10.5267/j.jpm.2021.7.003","DOIUrl":"https://doi.org/10.5267/j.jpm.2021.7.003","url":null,"abstract":"This study assessed the critical success factors (CSFs) of public-sector road construction projects execution from the perspective of definitive stakeholders associated with such projects by drawing on in-depth semi-structured interviews (16) and surveys (372) in Ghana, thirty-four (34) CSFs were identified. Using Relative Importance Index (RII), Spearman Rank Correlation Coefficients, and Kendall’s Coefficient of Concordance and the Chi-square test of significance statistics, the top ten most important factors in descending order are: the absence of political interference, project continuity by successive governments, adequate project funding, support from financial institutions and donor agencies and countries, government commitment to the project, absence of clientelism, absence of nepotism, no political corruption, payments of contractors on time and absence of court injunction or legal suit and land litigations. This study contributes to road construction CSFs in the context of public sector road construction in developing economies.","PeriodicalId":42333,"journal":{"name":"Journal of Project Management","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70781146","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}