全面生产性维修快速团队解决问题:沟通网络结构、媒体选择和团队效率

Jorge A. Colazo
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引用次数: 3

摘要

目的本研究旨在观察快速团队(ST)的绩效、沟通结构和媒体选择,以期从制造业的运营紧急情况中恢复过来。与这些特设团队相关的解决问题的过程包括早期阶段,主要目标是将过程恢复到工作状态,以及后期阶段,持续时间更长,找到并消除问题的根本原因。设计/方法论/方法基于工业制造运营的现场数据,作者通过回归模型检验假设。研究发现,在从早期到后期的演变过程中,媒体使用从高度同步转变为异步,团队协作网络的结构特征也发生了变化。当比较高表现球队和低表现球队时,这些影响是不同的。研究局限性/含义该研究仅包含一家公司的数据,限制了结论的外部有效性。样本主要为男性。研究中未包括的参与者流失和其他潜在协变量可能是额外的限制。实际含义更成功的团队更快地调整他们的沟通模式,从最初的分散组织转变为更集中的组织。网络模式的这些变化为ST的成功打开了一个新的视角,这是基于网络特征而非综合衡量。这些结论为干预措施提供了见解,这些干预措施可能会提高这些团队的成功率并减少生产线停机时间。原创性/价值据作者所知,在以往的研究中,操作性紧急问题解决过程中的两个阶段没有同时得到解决,本文试图将其作为主要的理论贡献。此外,以前关于ST成功的研究只关注影响有效性的综合措施,而从未关注其通信网络如何在解决问题的道路上发展。据作者所知,ST从一个相对无序的个人即兴聚集到一个有效的解决问题的组织的进化的网络观是首次提出的。
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Problem-solving by total productive maintenance swift teams: communication network structure, media choice and team effectiveness
PurposeThis study aims to look at the performance, communication structure and media choice for swift teams (STs) formed with the purpose of recovering from operational emergencies in manufacturing. The problem-solving process associated with these ad hoc teams include an early stage, where the main goal is to restore the process to working conditions, and a later stage, longer in duration, where the root cause of the problem is found and eliminated.Design/methodology/approachBased on field data from an industrial manufacturing operation, the authors test hypotheses by means of regression models.FindingsIt was found that in the evolution from early to later stage, media usage shifts from highly synchronous to asynchronous and the structural characteristics of the teams' collaboration networks mutate as well. These effects are different when comparing high- vs low-performing teams.Research limitations/implicationsThe study contains data for only one company, limiting the external validity of the conclusions. The sample was predominantly male. Participant attrition and other potential covariates not included in the study can be additional limitations.Practical implicationsMore successful teams adapt their communication patterns more rapidly, going from an initially decentralized organization to a more centralized one. These changes in network patterns open a new view of ST’s success, based on network characteristics rather than on aggregate measures. The conclusions yield insights for interventions that may increase the success rates of these teams and reduce production line downtime.Originality/valueThe two stages in the operational emergency problem-solving process have to the authors’ knowledge not been addressed simultaneously in previous research, which is attempted in this paper as its main theoretical contribution. Moreover, previous studies dealing with ST’s success have only looked at aggregated measures impacting effectiveness and never to how their communication networks evolve along the path to problem resolution. The network view of the evolution of the ST from a relatively disorganized impromptu agglomeration of individuals to an effective problem-solving organization is to the authors’ knowledge first presented.
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来源期刊
CiteScore
5.60
自引率
12.00%
发文量
53
期刊介绍: In today''s competitive business and industrial environment, it is essential to have an academic journal offering the most current theoretical knowledge on quality and reliability to ensure that top management is fully conversant with new thinking, techniques and developments in the field. The International Journal of Quality & Reliability Management (IJQRM) deals with all aspects of business improvements and with all aspects of manufacturing and services, from the training of (senior) managers, to innovations in organising and processing to raise standards of product and service quality. It is this unique blend of theoretical knowledge and managerial relevance that makes IJQRM a valuable resource for managers striving for higher standards.Coverage includes: -Reliability, availability & maintenance -Gauging, calibration & measurement -Life cycle costing & sustainability -Reliability Management of Systems -Service Quality -Green Marketing -Product liability -Product testing techniques & systems -Quality function deployment -Reliability & quality education & training -Productivity improvement -Performance improvement -(Regulatory) standards for quality & Quality Awards -Statistical process control -System modelling -Teamwork -Quality data & datamining
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