A system dynamics model of employees’ performance

Employee performance is dynamic and can have great impact on the overall performance of any company and its sustainability. A number of factors that can be controlled by the company can affect the employees’ performance. The present paper starts with a thorough literature review for identifying these key driving in order to develop a system dynamics models that will be able to assess different improvement scenarios and initiatives. Based on causal loop diagrams, stock and flow diagrams are developed and solved using system dynamics theory. The model developed can be used for organizations to assess the impact of different improvement initiatives

An ISM analysis of the critical success factors in ERP implementation

Enterprise Resource Planning (ERP) offers many benefits in aligning business operations. However, these implementations can be problematic and prone to failure. Critical success factors (CSF) which can improve the success rates of implementation have been researched and an interpretive structural modelling (ISM) was conducted to identify the interrelationships between factors. An ISM based model was created and this was achieved by completing the self-interaction matrix (SSIM), reachability matrix and level partitioning. This led to an ISM-based model being created followed by a cross-impact matrix multiplication (MICMAC) analysis to identify the factor’s relative driving power and level of dependence. The project revealed that top management support was the strongest CSF with a high driving power and low dependence. In addition, fourteen other factors displayed strong driving power with high dependence. The findings from the project were summarized into a recommended framework for manufacturing organizations to follow to increase the likelihood of a successful ERP implementation

Lean manufacturing, leadership and employees: the case of UAE SME manufacturing companies

Successful lean implementation to SMEs poses great challenges. Although lean principles, tools and strategies for implementation are widely known and well documented, companies still struggle. In the present paper, the challenges for the SMEs in their lean journey are discussed, focusing on leadership styles and their impact on how employees perform during the lean transition. The aim of the paper is to determine the extent to which the main principles of lean manufacturing are understood and adopted in manufacturing companies in a developing country such as the United Arabic Emirates (UAE) through a structured questionnaire. The degree of implementing lean manufacturing is assessed and discussed against literature review findings. Furthermore, the impact of various leadership styles during the lean transition is investigated. A second survey is used for capturing the current state with regards the employee performance and the role of leadership in manufacturing SMEs in the UAE

Machine learning algorithms comparison for manufacturing applications

With the vast amount of data available, and its increasing complexity in manufacturing processes, traditional statistical approaches have started to fall short. This is where machine learning plays a key role, addressing the challenges by bringing the ability to analyse large and complex datasets from multiple sources, finding non-linear and intricate patterns on data, relationships between several factors and their influence on the manufacturing process outputs. This paper demonstrates the advantages and applications of using supervised machine learning techniques in the manufacturing industry. It focuses on binary classification and compares the performance of three different machine learning algorithms: logistic regression, support vector machine, and neural networks. A case study has been conducted on a manufacturing company, using the techniques and algorithms mentioned. The case study focuses on analysing the relationship between different manufacturing process variables and their impact on one key output variable of a product, which in this case is the result of a quality test that measures product performance. The modelling problem has been oriented towards a Boolean goal to predict whether the parts will pass this test

Implementing pull manufacturing in make-to-order environments

The demand for increasing product variety and customization has forced many companies to adopt a make-to-order (MTO) strategy. Traditional push-type MTO companies suffer from unstable demands, struggling to deliver on time, making them consider the utilization of pull systems to control production. In the present paper, an overview of pull systems in MTO environments is presented. Moreover, a discrete event simulation (DES) model of an MTO company in the printing and packaging industrial sector was developed and validated, in order to identify areas for improvement. DES was also used in order to evaluate the feasibility of implementing three types of pull systems: kanban, CONstant-Work-In-Process (CONWIP) and Paired Overlapping Loops of Cards with Authorizations (POLCA). The main performance indicators measured were the average WIP and the average throughput time of parts. The key findings of this project for the case study were: a) kanban is inapplicable for the current routing of parts; b) a CONWIP strategy improves the shop floor performance, but only when extra capacity is added to the extrusion workstation; c) production based on POLCA leads to the blockage of the system due to the existence of multi-routes and undirected routing

Prioritized solutions for overcoming barriers when implementing lean in the healthcare supply chain: a Saudi perspective

The main purpose of this paper is to propose solutions for overcoming the obstacles that healthcare organizations might face when implementing lean. An in-depth review of existing barriers for lean implementation in healthcare supply chain is presented and validated by experts. Although there is a widespread use of lean concepts in developed countries, little attention has been paid to implementing a lean approach by healthcare providers in developing countries. The present study’s key novelty and contribution is related to this research gap. The study is thus focused in proposing solutions for healthcare organisations in developing countries, especially in Saudi Arabia. The efficacy of these solutions is assessed through experts’ opinion. The paper enhances the body of knowledge for the successful implementation of lean in a hospital settin

Feature reduction and selection for use in machine learning for manufacturing

In a complex manufacturing system such as the multistage manufacturing system, maintaining the quality of the products becomes a challenging task. It is due to the interconnectivity and dependency of factors that can affect the final product. With the increasing availability of data, Machine Learning (ML) approaches are applied to assess and predict quality-related issues. In this paper, several ML algorithms, including feature reduction/selection methods, were applied to a publicly available multistage manufacturing dataset to predict the characteristic of the output measurements in (mm). A total of 24 prediction models were produced. The accuracy of the prediction models and the execution time were the evaluation metrics. The results show that uncontrolled variables are the most common features that have been selected by the selection/reduction methods suggesting their strong relationship to the quality of the product. The performance of the prediction models was heavily dependent on the ML algorithm

A synergetic framework for green and lean manufacturing practices in SMEs: Saudi Arabia perspective

Manufacturers are urged to improve their sustainability performance, in terms of keeping the balance among economic, environmental, and social performances. Nevertheless, top managers and company leaders tend to complain that it is not possible to implement greener solutions without large investments. In this context, the well-known lean manufacturing approach, mainly focused on waste reduction, has come to be viewed with a renewed interest towards improving not only economic but also environmental and social aspects. Unfortunately, while there is no doubt that lean manufacturing increases productivity, efficiency, quality, and customers’ satisfaction by reducing wastes, there is a lack of research about the benefits of lean practices in relation to green manufacturing. The aim of the present work is to investigate the level of integration of green and lean manufacturing approaches, focussing specifically on the context of Saudi Arabia. As a result, a novel theoretical framework capable of combining the lean and green approaches within a synergetic environment, enhancing the former and mitigating the latter, is proposed. A survey was put together for assessing a number of hypotheses and validating the proposed framework. Qualitative analysis based on a survey conducted in different SME manufacturing companies in Saudi Arabia is presented. The statistical analysis of the collected data shows a clear trend that in Saudi Arabia, companies are starting to have a positive view about the integration of lean and green approaches implementation. The results highlighted higher maturity among the respondents with regard to the lean implementation, focussing on operational improvements. The improvements that can be attained with regard to environmental performance are coming next, and the framework proposed can help increase awareness among Saudi manufacturing SMEs

A conceptual lean implementation framework based on change management theory

Over the last two decades, numerous studies have been presented on the drivers and barriers that companies face when they try to implement lean. Such studies have mostly been based on conducting surveys through questionnaires and interviews, and have targeted specific industrial sectors and / or geographic boundaries. For helping companies implement lean, a number of frameworks have been developed. Most of them though, look like more as roadmaps, prescribing the sequence of the various lean tools that have to be adopted without considering the complexity of the human factor. It comes thus as no surprise, that many companies have failed and were not able to reap the benefits of lean manufacturing. In all literature reviewed, successful lean implementation is accompanied by a change in the way companies value the different dimensions of work. One of the major challenges of lean implementation is guiding the change journey as detailed in the implementation plan. Lean manufacturing requires change in structure, system, process, and employee behaviour. In the present paper, a conceptual framework based on change management theory is proposed and discussed