Pub Date : 2019-01-01DOI: 10.5267/j.jpm.2018.7.001
Aidin Delgoshaei, Armin Delgoshaei, Ahad Ali
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
32图1。也许，找到最优的工人数量是研究CMS中人力资源管理的主要思想。为了确定最优的操作员数量和零件分配，Park和Lee(1995)开发了一个两阶段模型，在第一阶段，使用田口法确定系统性能，然后将其作为分配模型的目标函数。赫迪(1997)研究了运营成本和外包成本之间节约成本最大化的概念。但他们的模型没有调查操作员水平、培训、招聘和解雇成本。Norman et al.(2002)提出了一个模型来分配制造单元中的工人，以最大化系统利润。Ertay和Ruan(2005)提出了确定操作员数量以最大化产出数量的想法。为此，使用加权输入数据，应用数据包络分析(DEA)。但在提出的模型中，考虑了所有操作人员和机器的相同技能。1.2技术工人的提升和分配，因为在实际工业中，操作人员的技能是不一样的，所以他们的产出是不一样的。Suer和Cedeño(1996)研究了考虑操作员级别的想法。为此，采用混合整数规划方法生成可选的操作符层次，然后采用另一整数规划方法寻找单元的最优操作符分配。Askin和Huang(1997)使用整数规划将工人分配到单元，以确定员工的培训计划。Aryanezhad等人(2009)考虑了工人的三个技能水平，这些技能水平可以通过培训在规划范围内提升。在此基础上，建立了同时进行胞体成形和工人分配的多周期调度模型。Jannes等人(2005)专注于将工人分配到团队工作中，目的是最大限度地减少培训和分配成本，以及最大限度地提高劳动灵活性。同年，Fitzpatrick和Askin(2005)认为，良好的团队组成要素不仅限于个人技能和特征，还包括技术和人际互动。因此，通过使用预先确定的技能水平度量，他们尝试选择工人并将他们分配到适当的小组中，以最大化团队绩效。Cesaní and Steudel(2005)重点研究了影响劳动力部署的一些因素。然后，他们将重点放在工作共享、工作平衡和平衡操作员分配(存在瓶颈操作)上。为了防止操作员超载和过度分配，Satoglu和Suresh(2009)在数学模型中使用了目标规划，其中目标是最小化工人的过度分配，交叉培训，招聘和解雇成本。1.3交叉培训的员工注意，交叉培训的员工是指那些接受过多项任务培训的员工。确定最佳的交叉训练工人组可以更灵活地提高系统性能。Bartholdi和Eisenstein(1996)发现，通过使用具有多个工作站和工人的大型工作单元，会自发产生稳定的工作划分和分配，使生产线平衡，生产率最大化。Kleiner et al.(1998)假设在一个基于计算机的系统中，典型的技术工人可以使用多功能机器执行多项任务。该模型的其他属性包括单元交货时间、零件运输距离、A. Delgoshaei等人/ Journal of Project Management 4(2019) 33工艺良率、操作员分类和劳动效率。在继续，Gel等人(2000)表明，交叉培训的员工可以比普通员工获得更高的绩效。Askin和Huang(2001)从不同的角度研究了贪婪、波束搜索和模拟退火对多目标优化模型的性能，该模型适用于工人团队的形成和元胞制造的交叉培训计划。Olorunniwo和Udo(2002)表明，高层管理角色和员工交叉培训对CMS的成功实施有显著影响。Kher (2000b)着重研究了在学习、再学习和流失条件下使用交叉培训工人获得的培训方案。在团队内分配技术工人和劳动力程度的想法属于Molleman和slop(1999)，他们指出上述项目对系统性能有重大影响。他们的研究结果表明，劳动力技能的均匀分布导致更好的系统性能，因此每个工人应该掌握相同数量的任务。后来，slop和Molleman(2000)在静态和动态两种情况下比较了基于瓶颈员工工作量的四种交叉培训政策。结果证实，通过使用更高水平的交叉培训员工，可以预期更好的团队绩效。 Jensen(2000)参与了部门、严格和混合单元布局中的人员配备水平和店铺布局。通过改变每个部门的员工数量，考虑3个层级的工作量平衡和2个劳动力转移规则，评估流程时间、延迟平均值和工作延迟的平方平均值。Li et al.(2012)专注于最小化平均工资，同时最大化平均满意度。为此，他们提出了一种多目标混合整数规划方法，以确定柔性装配单元布局中交叉训练的劳动力数量和必须分配给劳动力的任务。他们研究的另一个贡献是考虑了员工的满意度和任务冗余水平。1.4双资源问题双约束资源问题是指同时在机器和工人上调度零件的问题。Kher (2000a)调查了交叉培训工人在学习、再学习和自然流失条件下获得的培训方案。Kher et al.(1999)进一步得出结论，交叉培训的有效性在很大程度上取决于员工的现有遗忘率。此外，他们还评论了批量大小与工人灵活性之间的显著关系。交叉培训包括可变性、劳动力互动、资源利用和过渡效率。Molleman & Slomp(1999)指出，团队内部的技能分布和员工多功能性的程度对系统性能有显著影响。他们的发现表明，统一的劳动力技能分配导致更好的系统性能。换句话说，每个工人应该掌握相同数量的任务。Xu et al.(2011)对双资源系统进行了新颖的研究。Hamedi等人(2012)开发了一个模型，其中零件，机器和工人被分组并同时分配到生成的虚拟单元。然后，通过多目标禁忌搜索算法求解所建立的模型，找到近似最优解。在HRM-CMS中考虑动态部件需求会导致系统不平衡的想法尚不成熟。为了解决这个问题，Mahdavi等人(2010)开发了一个多模式规划模型，用于将工人分配到可重构CMS中的单元。在提出的模型中，雇用、解雇和工资成本被认为是总系统成本的一部分。他们的模型的另一个贡献是考虑了工人的可用时间。如前一节所述，Mahdavi等人(2012)专注于在特定机器上加工时工人和零件的细胞间运动。Min和Shin(1993)认为熟练的人力资源是细胞形成过程的一部分。他们的目标是寻找具有类似专业知识和技能的机器操作员来生产类似的零件系列。Black和Schroer(1993)研究了一种多功能操作员可以在细胞内行走以完成操作的情况。他们报告说，使用便携式工作站可以提高生产率。Morris和tersin(1994)研究了劳动力和设备在双重约束资源规划中的影响，以比较工艺布局和单元布局。Hyer et al.(1999)进行了一项考虑细胞系统中8个人为因素的实地研究，发现不同人为因素可能影响CMS的重要性。因此，他们得出结论，通信和团队工作是34个使用细胞系统的最重要因素。Cesaní和Steudel(2005)开发了一个基于人力资源因素的CMS中工人分配的两阶段框架工作。在第一阶段，他们进行了实证调查，以找到影响劳动灵活性的重要因素。在第二阶段，他们利用这些因素在细胞中找到最佳的工人分配。他们研究的贡献是在操作员的工作量、机器共享的水平和类型之间找到平衡，以提高基于单元的系统的性能。Chakravorty和Hales(2004)提供了一个案例研究来调查工人分配对住宅和轻型商业建筑产品制造商和供应商系统性能的影响。随后，Chakravorty和Hales(2008)报道，在细胞形成后的早期工作阶段，既存在技术故障，也存在人力资源错误。然而，经过一
{"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}
Pub Date : 2019-01-01DOI: 10.5267/J.JPM.2018.12.001
M. O. Babatunde, D. Ighravwe
{"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}
Pub Date : 1900-01-01DOI: 10.5267/J.JPM.2019.1.003
E. M. González-Neira, J. Montoya-Torres
{"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}
Pub Date : 1900-01-01DOI: 10.5267/j.jpm.2021.7.003
I. S. Damoah, Anthony Ayakwah, Paul Twum
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.
{"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}
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