Computer Simulation to Manage Lean Manufacturing Systems

There is a difference between a lean manufacturing system and a manufacturing system that just applies lean techniques. This paper addresses the previous statement through using computer simulation to explore the impact of applying just in time lean policy on a traditional inventory based production system. A system dynamics model is introduced to capture the different components of the production system. The inventory dynamics of the modeled system is examined against different production scenarios under stochastic demand. Results showed that in systems that are not fully transferred to lean, adopting lean principles are not always beneficial. The paper suggests some specific management policies for successful lean application within the scope of the modeled manufacturing syste

Assessing Lean Systems Using Variability Mapping

A new approach to assess lean manufacturing based on system\u27s variability is proposed. The assessment utilizes a new tool called variability source mapping (VSMII) which focuses on capturing and reducing variability across the production system. The new tool offers a new metric called variability index to measure the overall variability level of the system. Based on the mapping and the new metric, VSMII suggests a variability reduction plan guided by a recommendation list of both lean techniques as well as production control policies. An industrial application is used to demonstrate the new tool. Results show that VSMII managed to reduce the overall variability level of the system as well as non-value added activities. Finally, the new variability index was successfully applied as a leanness assessment metric

Insights on lean gamifications for higher education

Purpose There is no argument that using games (gamification) is an efficient way of learning in higher education. The questions, though, are which gamification approach is most suitable at that level and how to assess its suitability? This paper aims to attempt to partially answer these two questions, in the context of lean thinking education. Design/methodology/approach The paper offers an assessment criteria to investigate the impact of lean gamification based on the evaluation of motivational, cognitive and social processing during games. In addition, a study is conducted among selected games using these assessment criteria. The study included statistical as well as comparative analysis. The study was based on a sample of undergraduate students learning various lean thinking concepts through physical games over the course of six months. Findings Results showed different interaction levels between the three evaluation criteria depending on the type and design of the lean game. The reported scores and analysis drew various lessons on how to use gamification in the context of lean teaching, outlined some best practices in lean games design and suggested recommendations in mapping lean games from industrial domain to higher education domain. Research limitations/implications The scope of this research was bounded by the sample size of students as well as the selected nine lean thinking games. Larger pool of students as well as other lean thinking games can offer further insights and confirm the outlined ones. Practical implications The presented work will help lean thinking educators in higher education to better understand the student dynamics associated with engaging them in this type pf pedagogical approach. It will help guiding lean thinking games’ designer on how to better cater for this segment of lean thinking learners. Finally, it will aid in promoting lean gamification as an effective learning tool. Social implications The social impact is achieved through enhancing lean thinking education to a wide number of students. This will positively impact the society through the application of the effective lean tools at different stages, levels and places in these students’ life experiences. Originality/value This study offers one of the very few applications in gamification assessment in the context of lean thinking. Furthermore, it integrates the social processing criterion for the first time with the classical two other criteria (motivation and cognitive) used in games education assessment. Finally, it offers new insights for lean thinking game designers for higher education learners

Dynamic analysis of a lean cell under uncertainty

One of the ultimate targets of lean manufacturing paradigm is to balance production and produce at takt time in production cells. This paper investigates the performance of a lean cell that implements the previous lean goals under uncertainty. The investigation is based on a system dynamics approach to model a dynamic lean cell. Backlog is used as a performance metric that reflects the cell’s responsiveness. The cell performance is compared under certain and uncertain external (demand) and internal (machine availability) conditions. Results showed that although lean cell is expected to be responsive to external demand with minimum waste, however, this was not the case under the considered uncertain conditions. The paper proposes an approach to mitigate this problem through employing dynamic capacity policy. Furthermore, the paper explores the effect of the delay associated with the proposed capacity policies and how they affect the lean cell performance. Finally, various recommendations are presented to better manage the dynamics of lean manufacturing systems

A system model for green manufacturing

Manufacturing systems evolution is afunction in multiple external and internal factors. With today’s global awareness of environmental risks as well as the pressing needs to compete through efficiency, manufacturing systems are evolving into a new paradigm. This paper presents a system model for the new green manufacturing paradigm. The model captures various planning activities to migrate from a less green into a greener and more eco-efficient manufacturing. The various planning stages are accompanied by the required control metrics as well as various green tools in an open mixed architecture. The system model is demonstrated by an industrial case study. The proposed model is a comprehensive qualitative answer to the question of how to design and/or improve green manufacturing systems as well as a roadmap for future quantitative research to better evaluate this new paradigm

Capacity scalability modeling and design framework for reconfigurable manufacturing systems.

The focus of this research will be on how to approach the design reconfigurable manufacturing systems and how to control the design process. This will be achieved first in a systematic manner through implementing system design methodology to develop an architecture that visualizes the full reconfiguration process from recognizing customer needs through the operational level. An example in the reconfigurable printed circuit board (PCB) automatic assembly industry is used to illustrate the design and control activities in the proposed architecture. An analytical approach will follow the systematic approach. In this research only the first layer of the architecture dealing with capacity scalability is mathematically modeled. The capacity scalability model is used to develop a computer-based tool that generates optimal capacity scalability schedule and can be integrated to the architecture. Results of using the developed tool with numerical examples revealed the need to modify cost function of the model to reflect the real case of capacity scalability in reconfigurable manufacturing systems. The modification highlighted the fact that the success of reconfigurable manufacturing systems is through responsive scalable systems in a cost effective manner. Results also showed the superiority of the generated optimal capacity scalability schedule over other capacity plans and illustrated how the developed model can deal with different demand scenarios in an optimal way. (Abstract shortened by UMI.)Dept. of Industrial and Manufacturing Systems Engineering. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2003 .D45. Source: Masters Abstracts International, Volume: 43-01, page: 0293. Adviser: Waguih El-Maraghy. Thesis (M.A.Sc.)--University of Windsor (Canada), 2004

The association between personality, coping and depressive symptoms in adult patients with chronic pain

As a rising concern in the medical and mental health fields, this study aims to examine predictors of depressive symptoms in a sample of Egyptian chronic pain patients in terms of coping styles and personality traits. Patients with chronic pain are believed to experience different stressors which include, but are not limited to, pain, disability, reduced productivity and financial difficulties. Such factors, in addition to various psychosocial factors, constitute the disease burden of chronic pain. This study examines the degree to which coping styles and personality traits can influence the disease outcome in terms of comorbid depressive symptoms. A total of 98 (50 patients with fibromyalgia and 48 patients with rheumatoid arthritis) patients were interviewed and were assessed in terms of their coping styles, personality profile and severity of depressive symptoms. Results show a high prevalence of depressive symptoms and suggest passive coping, high neuroticism, low extraversion, unmarried status and more years of education. to be moderate predictors of the severity of chronic pain. Findings of this study shed light on the significance of the psychological aspects of chronic pain conditions and may help in designing liaison interventions for the management of secondary and comorbid depressive symptoms

Understanding AI Application Dynamics in Oil and Gas Supply Chain Management and Development: A Location Perspective

The purpose of this paper is to gain a better understanding of Artificial Intelligence (AI) application dynamics in the oil and gas supply chain. A location perspective is used to explore the opportunities and challenges of specific AI technologies from upstream to downstream of the oil and gas supply chain. A literature review approach is adopted to capture representative research along these locations. This was followed by descriptive and comparative analysis for the reviewed literature. Results from the conducted analysis revealed important insights about AI implementation dynamics in the oil and gas industry. Furthermore, various recommendations for technology managers, policymakers, practitioners, and industry leaders in the oil and gas industry to ensure successful AI implementation were outlined. Doi: 10.28991/HIJ-SP2022-03-01 Full Text: PD

Dynamic modelling of impact of lean policies on production levelling feasibility

A dynamic systems approach is proposed to investigate challenges of implementing production leveling and associated costs. A model of a lean cell is developed using system dynamics. The model captures various lean tools influencing production leveling. Comparative cost analysis between various leveling implementation policies for stochastic demand with multiple products is conducted. Results showed that determining the most feasible leveling policy is highly dictated by both capacity scalability cost and limitations. The developed model and revealed insights can help lean practitioners to better decide on when and how to implement production leveling as well as determine production lots sizes

Developing a Greenometer for green manufacturing assessment

In this paper a toolbox (Greenometer) to assess the greenness level of manufacturing companies is proposed. The assessment approach is based on capturing the relative greenness position of any company among other industries from different sectors as well as within the same sector. The assessment was based on selected greenness attributes and their composing indicators at each of the two levels of the developed Greenometer. Geometric Mean Method (GMM) was adopted to be the generic assessment technique for cross industries greenness evaluation, while Data Envelopment Analysis (DEA) was employed to assess the greenness level of intra-industries layer. Three different industrial applications were used to demonstrate the applicability of the developed Greenometer. Results highlighted how the proposed tool can be a useful for manufacturing managers not only in understanding their green performance position at various levels, but also aiding them in their green transformation/improvement efforts. Specifically, the Greenometer assessment scores will help in setting plans through highlighting prioritized areas of required improvement as well as offering quantitative targets and tracking metrics along the transformation journey