This paper describes the p-diagram (parameter-diagram) and its application in planning a DoE (Design of Experiments). A case study describing an actual problem from industry is presented where the planning phase started to go wrong as difficulties in selecting the right variables for the DoE were discovered. Furthermore, running these experiments became prohibitively expensive, due to the large number of such experiments that would be needed, and though the exploitation of a p-diagram it was then possible to come up with a feasible DoE.

Environmental awareness among the masses compelled many companies to adopt sustainable practices in their business operations. Remanufacturing is a well-tested and successful business model practiced in many European countries. But in many African and Asian countries, it is still nascent, including India. This research study tries to identify the critical factors in the “Operational Management” area for the viability of remanufacturing business in India. For this purpose, a questionnaire was developed based on the important factors identified from the extensive literature review. An online questionnaire survey was conducted among Indian white goods appliance manufacturing companies and their suppliers. The responses were analyzed statistically and ranked based on their criticality in initiating remanufacturing business in India. The findings may help the Indian government and manufacturing firms to frame proper strategies related to the operational management issues of remanufacturing business in India.

In sequencing situations, it may affect parameters used to determine an optimal order in the queue, and consequently the decision of whether (or not) to rearrange the queue by sharing the realized cost savings. In this paper, we extend one machine sequencing situations and their related cooperative games under fuzzy uncertainty. Here, the agents costs per unit of time and processing time in the system are fuzzy intervals. In the sequel, we define sequencing fuzzy interval games and show that these games are convex. Further, fuzzy equal gain splitting rule is given. Finally, a numerical example is illustrated priority based scheduling algorithm.

This paper uses a Genetic Algorithm (GA) to reduce total tardiness in an identical parallel machine scheduling problem. The proposed GA is a crossover-free (vegetative reproduction) GA but used for four types of mutations (Two Genes Exchange mutation, Number of Jobs mutation, Flip Ends mutation, and Flip Middle mutation) to make the required balance between the exploration and exploitation functions of the crossover and mutation operators. The results showed that use of these strategies positively affects the accuracy and robustness of the proposed GA in minimizing the total tardiness. The results of the proposed GA are compared to the mathematical model in terms of the time required to tackle the proposed problem. The findings illustrate the ability of the propounded GA to acquire the results in a short time compared to the mathematical model. On the other hand, increasing the number of machines degraded the performance of the proposed GA.

Production problems have a significant impact on the on-time delivery of orders, resulting in deviations from planned scenarios. Therefore, it is crucial to predict interruptions during scheduling and to find optimal production sequencing solutions. This paper introduces a selflearning framework that integrates association rules and optimisation techniques to develop a scheduling algorithm capable of learning from past production experiences and anticipating future problems. Association rules identify factors that hinder the production process, while optimisation techniques use mathematical models to optimise the sequence of tasks and minimise execution time. In addition, association rules establish correlations between production parameters and success rates, allowing corrective factors for production quantity to be calculated based on confidence values and success rates. The proposed solution demonstrates robustness and flexibility, providing efficient solutions for Flow-Shop and Job-Shop scheduling problems with reduced calculation times. The article includes two Flow-Shop and Job-Shop examples where the framework is applied.

The paper presents a method for improving the lime production process by increasing the efficiency of the lime slurry transport that occurs in it. The aim of the study was to reduce the energy demand of the pump installed in the discharge line. The presented solution consists of applying an additive called deflocculant to the transported slurry in order to reduce its viscosity while increasing the concentration of solids content. The deflocculant applied to the slurry is composed of waste material from the lime slaking process and an environmentally neutral chemical substance in the form of sodium-water glass. The rheological studies conducted confirm the positive effect of the selected deflocculant on the properties of the slurry tested. As a result of the analysis, it has been shown that the proposed solution has a substantial effect on reducing the friction factor of the transported slurry, thus reducing the energy consumption in the investigated process.

This research addresses an inventory classification problem in a company that manufactures plastic pallets. Classification of the inventory is difficult because it is subject to two restrictions: the number of changeovers and the size of inventory storage. A mathematical model is first proposed to maximize the fill rate by classifying all product items into four groups. Due to all items can be classified based on the monthly demand, in descending order. The present study then proposed a procedure to find the classification that is most efficient. According to the experimental results, the maximum fill rate in the current situation is 89.85%. The proposed methodology also tested different production batches and levels of demand. The proposed methodology was found to be appropriate for practical application.

This study was conducted in a company that produces palm oil-based products such as cooking oil and margarine. The study aimed to encounter defects in packaging pouches. This study integrated the overall equipment effectiveness (OEE) with the six sigma DMAIC method. The OEE was performed to measure the efficiency of the machine. Three factors were measured in OEE: availability, performance, and quality. These factors were calculated and compared to the OEE world-class value. Then, the Multiple Linear Regression was performed using SPSS to determine the correlation between measurement variables toward the OEE value. Lastly, the six sigma method was implemented through the DMAIC approach to find the solution and improve the packaging quality. Supposing the recommendations are implemented, the OEE is expected to increase from 82% to 85%, with availability ratio, performance ratio, and quality ratio at, 99%, 86%, and 99.8%, respectively.

The article presents a business model based on an industrial network of companies capable of producing personalized products in an Industry 4.0 environment. Based on research conducted in Poland, in manufacturing companies, the critical problems associated with the implementation of Industry 4.0 technologies and the expected benefits associated with their implementation are addressed. The model’s task is to integrate a customer expecting personalized production with a network of companies with the appropriate production resources. The original achievement is the integration of the customer and the manufacturer around an e-business platform, which allows the rapid prototyping of a network of SME companies capable of realizing personalized production. The proposed model describes the architecture of enterprise cooperation under the conditions of implementing the Industry 4.0 concept and is dedicated to the SME sector. The model provides a basis for building prototypes of e-business platforms of small and medium-sized enterprises.

The engine is the most important component of a vehicle. It attaches to the main frame via the engine mounting bracket which supports weight and operating loads. The engine mount therefore plays a crucial role in the durability and comfort of the vehicle. This article contributes to the search for the most optimal model from the point of view of resistance, environmental impact, and manufacturing cost. This involves, on the one hand, optimizing the support by reducing its initial mass by 30%, and on the other hand, seeking suitable material and manufacturing process with the least environmental impact. To this end, topology optimization will be combined with an environmental assessment and a manufacturing cost analysis. Four materials will be tested and evaluated. Finally, a cost analysis will present a comparison between a conventional process and 3D printing.

Management and Production Engineering Review (MPER) is a peer-refereed, international, multidisciplinary journal covering a broad spectrum of topics in production engineering and management. Production engineering is a currently developing stream of science encompassing planning, design, implementation and management of production and logistic systems. Orientation towards human resources factor differentiates production engineering from other technical disciplines. The journal aims to advance the theoretical and applied knowledge of this rapidly evolving field, with a special focus on production management, organisation of production processes, management of production knowledge, computer integrated management of production flow, enterprise effectiveness, maintainability and sustainable manufacturing, productivity and organisation, forecasting, modelling and simulation, decision making systems, project management, innovation management and technology transfer, quality engineering and safety at work, supply chain optimization and logistics. Management and Production Engineering Review is published under the auspices of the Polish Academy of Sciences Committee on Production Engineering and Polish Association for Production Management. The main purpose of Management and Production Engineering Review is to publish the results of cutting-edge research advancing the concepts, theories and implementation of novel solutions in modern manufacturing. Papers presenting original research results related to production engineering and management education are also welcomed. We welcome original papers written in English. The Journal also publishes technical briefs, discussions of previously published papers, book reviews, and editorials. Letters to the Editor-in-Chief are highly encouraged.

The main goal of the research is to develop a set of guidelines for the development of business within the framework of the green industry, in compliance with all current environmental regulations, as applied to the realities of the current economic situation in China. The methodology basis is a combination of system analysis of the key principles of business development within the framework of environmental strategy in China with a comprehensive analysis of green industry concept as a factor limiting the activities of enterprises to avoid environmental pollution. The results obtained in the research indicate the presence of significant results in the interaction of government and business in the framework of mutually beneficial collaboration for the growth of the green industry. Chinese business structures invest in the development of “green” industrial and manufacturing technologies while ensuring the necessary level of environmental protection.