Decision Making in Manufacturing and Services

Resilience of Robotic Solutions in Extreme Conditions

Dariusz Sala — 2024-07-29

The study is devoted to the problems of using modern advanced technologies by logistics companies aimed at increasing the speed of technological operations and transforming business processes aimed at reducing financial costs, increasing the efficiency of the use of labour resources, and minimizing risks. Today, this is a decisive factor in increasing the company's competitiveness in the market, increasing profitability, and realizing long-term leadership. Innovative logistics is an effective tool for streamlining flow processes through the introduction of high-tech innovations in the operational and strategic management of market structures, which are aimed at improving the quality of customer service, increasing the efficiency of flow processes and reducing the total cost of their implementation in order to achieve key business objectives.
The paper examines approaches to the automation of business processes in the logistics sector, in the context of robotization of technological operations, taking into account the features due to the functioning of enterprises under the conditions of constant exposure to extreme risks. The concept of robotization of processes has been developed, which will increase the productivity and efficiency of business, help reduce operating costs, reduce the likelihood of personnel errors and contribute to improving business security. The results are implemented in the practice of a number of logistics companies in the real sector of the economy.

Six Sigma vs. other quality improvement tools A comparative analysis of trends in years 1985-2024

Marcin Nakielski — 2024-07-29

Six Sigma is a widely adopted method in various industries that is aimed at process improvement and quality management. Understanding Six Sigma's evolving interest and utilization can provide valuable insights into its current significance and prospects. Using data from Google Trends, Google Books, Web of Science, and Scopus, this study examined the search volumes and interests in keywords and phrases that were related to Six Sigma over a specified period. The global analysis revealed the overall direction of interest in Six Sigma worldwide, highlighting periods of peak interest and potential significant shifts in the method’s popularity. By identifying those times with the highest concentrations of interest, the article provides a deeper understanding of the adoption and perception of Six Sigma. On top of this, Six Sigma was compared in popularity (by trends) with other known methods such as Lean, Kaizen, PDCA, and TQM. This research contributes to the existing body of knowledge by shedding light on the current trends and future directions of Six Sigma globally. The findings offer valuable insights for practitioners, researchers, and organizations that seek to leverage Six Sigma for process improvements and quality management.

Predictions and Application of Queueing Analysis: A Case of Regional Hospital Limbe, Cameroon

Daphne T. Machangara — 2024-12-12

In this work, we apply queue analysis and the prediction of waiting time at the Regional Hospital Limbe (RHL). The main purpose of the work was to be able to make mathematical sense of a real-life scenario concerning queues (waiting lines) and to try to come up with models for performance measurement and improvement. This can be achieved using queueing theory concepts, composed of queueing models that provide some operational insights because of their analytical nature. The observations included studying patient arrival and waiting times, together with doctor service times. The results show the busy departments in the hospital, busy days, and busy times. Long waiting times were found to exist mainly in general practitioner (GP) and specialist consultations. The queueing concept was applied to only one service segment, GP consultation. Although strong scientific conclusions cannot be made on the queuing models obtained due to inefficient data, the value of this work lies mainly in the methodology and proposal of different operating systems that can be adopted. Furthermore, some predictions were made using machine learning to see how long a patient can wait in a queue for service, the model predicting with an average of 10 minutes and 53 seconds of error.

Analyzing Activities of Mobile App Users Who are Preparing for Driving Tests as Sources of Knowledge about Consumer Behavior

Anna Zapiór — 2024-12-12

This article presents the partial results from ongoing research that uses mobile applications that help individuals prepare for their driving license exams. The aim of the presented research is to analyze the activity of the users of these applications (including their daily activities, any tasks that are performed, and the lengths of times that are spent on sample exams and tests). The theoretical implication of the article is to draw attention to the time of the highest consumer activity, while the practical implication is to emphasize the importance of using ICT (particularly, mobile applications) in knowledge and information management, marketing decision-making, and education.

Application of Basic Machine-Learning Classifiers for Automatic Anomaly Detection in Shewhart Control Charts

Aleksander Woźniak — 2024-12-12

In today’s dynamic technological environment, innovation plays a crucial role – especially for manufacturing enterprises that constantly strive to improve the quality of their products. This article examines the quality-management issue in a company producing car rims. It was identified that real-time quality control can sometimes be unreliable due to controller fatigue, leading to erroneous data interpretation or delayed responses to deviations in the production process. The study aimed to investigate the possibility of eliminating or significantly reducing these errors by employing a tool that is based on artificial intelligence. The article covers the preparation of training data, the training of classifiers, and the evaluation
of their effectiveness in analyzing control charts in real time. The adopted hypothesis assumes that machine-learning classifiers can be effective methods of support for quality controllers. The research began with collecting measurement data from the machine and dividing it into training and test sets. The obtained results were evaluated using standard quality measures for machine-learning models. The results showed that the use of artificial intelligence can bring significant benefits in improving quality supervision in the production process of car rims.

Modeling the Market Value of a Product Based on New Technologies - Preliminary Tool Concept

Paweł Filipowicz — 2024-12-20

Changes in the way market advantage is achieved and the emphasis on value creation that has been introduced by technological change are forcing companies to seek new and effective management tools when it comes to innovative activities; hence, the discussion and presentation of the conceptualization of such a decision-making model. Its basic premise is to take the technology life cycle as a determinant of the market diffusion of a product based on the use of new technologies. Consequently, a decision matrix is developed – one dimension of which is innovation measured by the dynamics of technical debt and the other by customer-perceived value. The product as an analytical object is considered as the sum of the utility functions while allowing for each utility function to originate from the use of a different technology (which is in an adequate phase of its life cycle). After presenting the theoretical model, an example of an analysis of a fictitious product is given, which is a device for cooling and printing food substances. The presented analysis example shows the practical possibilities of using the developed decision-making tool in the areas of the technological and
marketing activities of the enterprise and, in particular, the design of new products or new utility functions.