Production Planning

Production planning in the primary aluminum industry is a critical task, due to heavy imbalances among the main processes. As liquid production (reduction) has a very continuous and stable output, solidification at different lines have different operational paths (batch/continuous), shutdowns and variations in rates. Due to material's nature (hot liquid metal), it is not possible to maintain a buffer to absorb those imbalances. An adequate logistics planning for distributing liquid metal has to accomplish the solidification plan with an adequate usage of resources. In this paper we present the application of a simulation model to identify the main bottlenecks in the process, analyze dynamic system behavior, apply heuristics balancing algorithms and validate possible solutions for increasing casting capacity. The simulation model was implemented at Aluar's plant.

In this paper we describe a first attempt to solve planning problems through an Ant Colony Optimization approach. We have implemented an ACO algorithm, called ACOPlan, which is able to optimize the solutions of propositional planning problems, with respect to the plans length. Since planning is a hard computational problem, metaheuristics are suitable to find good solutions in a reasonable computation time. Preliminary experiments are very encouraging, because ACOPlan sometimes finds better solutions than state of art planning systems. Moreover, this algorithm seems to be easily extensible to other planning models.

This research describes how MSMEs in the children's clothing industry implement these three strategies. In Level Strategy, production is kept at a constant level, using inventory as a buffer. In the Chase Strategy, production is matched directly to demand, reducing inventory and carrying costs. In Mixed Strategy, the combination of strategies allows flexible response to demand fluctuations, minimizing inventory costs. The calculation results show that using Mixed Strategy allows companies to optimize production, reduce inventory costs, and respond quickly to variations in market demand. The total costs during this period were the result of production costs, inventory costs, overtime costs, and worker salaries, reaching a total of IDR 124,900,000. This research provides insight into how MSMEs can utilize aggregate planning with various strategies to increase their operational efficiency and flexibility in facing market dynamics. Penelitian ini menyelidiki efektivitas penggunaan Aggregate Planning pada industri Usaha Mikro, Kecil dan Menengah (UMKM). Melalui tinjauan literatur menggunakan artikel jurnal ilmiah nasional dan internasional tahun 2018-2023, penelitian ini mengidentifikasi tiga pendekatan utama dalam perencanaan agregat: Level Strategy, Chase Strategy, dan Mixed Strategy. Level Strategy menjaga tingkat produksi pada tingkat yang konstan, menggunakan inventaris sebagai penyangga untuk menghadapi fluktuasi permintaan. Strategi Chase

This chapter is about production planning optimization modeling in the production centers in a demand and supply chain manufacturing, distributing and selling high value consumer products. First, it contrasts demand and supply chain alternatives in terms of collaboration, agility, customer-centricity and personalization offering, with a focus on the implications for production planning optimization. Second, it introduces a comprehensive production planning optimization model applicable to a large variety of centers in demand and supply chains. Third, it contrasts the production planning optimization model instance required as a demand and supply chain is transformed from a rigid and pushy implementation to integrate more collaboration, customercentricity, agility and personalization. It also puts in perspective the importance of production planning optimization knowledge and technology. Finally it draws conclusive remarks for the research and professional communities.

Contemporary manufacturing companies are navigating industrial digitalization anticipating increased production efficiency and competitiveness in a volatile environment. This study focuses on the implementation processes of digital tools for production planning and control (PPC), i.e., advanced planning and scheduling (APS) software, in relation to the application of analog planning with physical flow boards. Digital tools can support understanding the consequences of production changes and variations, hence facilitating adaptable and resilient manufacturing. However, technological changes can be daunting, and effective implementations require dynamic capabilities to remain competitive in elusive environments. The aim is to study the implementation processes of an APS software to understand the requirements of fruitfully moving from analog planning to next-generation digital tools for decision support in PPC. The paper presents an explorative case study, at a manufacturing company w...

Raw material inventory management is a crucial element in the food industry to ensure smooth production processes. Unstable inventory can lead to risks of material spoilage, stock shortages, and quality degradation, which impact the fulfillment of market demand. The Fuzzy Logic method, specifically Fuzzy Sugeno, is used to address the complexity and uncertainty in inventory management. This method allows inventory data to be processed more flexibly, producing accurate numerical outputs that can be directly applied to operational decisions. This study employs a descriptive qualitative approach with a literature review to examine the role of Fuzzy Logic in decision-making related to raw material inventory, along with data analysis of production in the food industry. Production data for pie crusts from April 2023 to May 2024 shows inventory fluctuation patterns, with initial stock ranging from 996 to 1153 units, production from 300 to 1579 units, and incoming stock from 310 to 1535 units each month. Through the application of Fuzzy Sugeno, initial stock, production, and incoming stock membership values are categorized into fuzzy sets (low, medium, and high) to map uncertainty in input data. Implementing Fuzzy Sugeno on MATLAB generates more precise outputs aligned with inventory management needs in the food industry. The results indicate that using the Fuzzy Sugeno method can improve stock prediction accuracy and reduce the risk of overstocking or understocking, supporting more efficient and stable operations. This approach provides an adaptive solution to market demand changes, essential for business sustainability and production stability in the food industry.

The revolution in automation and robotics is a fact today. The ROBOMINERS project is moving in this direction. The aim of the project is to develop a small mining robot that will be able to explore hard-to-reach deposits completely autonomously. Currently, tests of the robot's locomotion in the mine, as well as mineralogical, geophysical sensors and production tools have been successfully completed. Since it is generally accepted that replacing humans with robots is economically justified, in the article asks whether there is also a justification for the impact on the environment. For this purpose, a variant environmental impact assessment (EIA) of the use of the robot in a mining environment was carried out. The three variants differed in the degree of development of the facility, geological structure and depth of occurrence. Compared to a conventional underground mine, the robot will be much more environmentally friendly. It will deliver only the richest ore to the surface, which will result in several times less waste. Surface destruction, noise emission and environmental pollution will be irrelevant to existing forms of land development. European legislation is included, which is constantly aimed at protecting the heritage that is our planet. The provisions of the laws of the European Union and its selected members were analysed: Czech Republic, Hungary, Poland and Portugal. The assumption is that the robot could replace the construction of an underground mine, which always has a significant impact on the environment. The result is very optimistic and at this stage of work it may open new opportunities for sustainable mining in Europe and around the world.

The paper describes an experimental multi-agent system developed for and aimed at a computer-supported project-oriented production planning. The system is based on a heterogeneous hierarchy of agents of three types that reflect the managerial structure of the manufacturing enterprise. To improve the system efficiency, a new formalism}called tri-base model}of the multi-agent internal communication/negotiation mechanism has been introduced. The tri-base model that has been tested in an industrial environment is treated in detail in the paper.

This article describes a methodical framework that combines two specific methods of Lean management, namely the ABC method and the MRP planning method. The article further argues that combining the ABC inventory method with subsequent MRP planning is beneficial if the combination is implemented in practice. To demonstrate the benefits, the framework is tested using a case study company. The presented case-study problem is to reduce the number of changeover downtimes in the environment of an engineering production company. The researched company deals with the problem of setting up production lines in a way to minimize the number of downtimes within one work shift. Within the solution, four possible variants of the production plan are presented. By combining the ABC and MRP methods, up to four changeovers can be saved, which in financial terms represents a saving of about EUR 450,000 per year.

In this article we give an overview of the relation between planning of maintenance and production. On the one hand we consider production planning and scheduling models where failures and maintenance aspects are taken into account. Next we discuss the planning of maintenance activities, where we consider both preventive as well as corrective maintenance. Thirdly, we consider the planning of maintenance activities at such moments in time where the items to be maintained are not or less needed for production, also called opportunity maintenance. Apart from describing the main ideas, approaches and results we also provide a number of applications.

Manufacturers in high-volume settings focus on flexible sampling to improve quality. This research compares adaptive strategies with fixed plans. We evaluate how these methods perform in real-world settings. This work looks at speed, cost, and results. It checks how well they adapt to new situations. This study is needed. Production grows larger and more complex every day. Fixed plans follow set rules. They do not adjust for changes in production or new data. This rigidity causes waste. Plans might check too many or too few parts. Adaptive sampling allows for real-time changes based on current findings. These adjustments make quality control faster and products more reliable. Moving to flexible sampling has many benefits. It helps daily work and keeps a company competitive. This study looks at how companies use SAP Quality Management (QM) systems. These systems provide a way to use flexible sampling. SAP QM connects quality tasks to factory management.

SAP Quality Management (SAP QM) and SAP Production Planning (SAP PP) work together for quality control. This link is key in today's factories where people need high quality and fast work to meet their goals. People want top products and fast results at the same time. This setup helps managers watch and control product quality at every step of the work. Companies create a clear path for data to move between SAP QM and SAP PP. This helps them use strict quality rules that match their daily work. They waste less and use their tools and materials better. Research shows that good quality management cuts scrap rates and boosts work speed. It improves products. This proves these systems matter in a tough market. Checking quality during the process helps people make fast decisions and workers fix problems right away. Live data helps staff change the production line right away to keep quality standards high.

This dissertation examines how Digital Twin technology joins with SAP Quality Management (QM) systems. It aims to improve how factories predict defects in manufacturing processes. The work focuses on how current methods fail to use realtime data for good defect detection. The study shows how to build a strong predictive framework for these processes. It combines factory data, defect logs, and performance numbers from SAP QM with simulation data from Digital Twins. The results show that defect rates dropped by up to 30 percent. Teams responded much faster to potential quality problems. These results prove that combining these systems works well. The meaning of these results goes beyond just manufacturing. They suggest big changes for the healthcare industry. Hospitals need quality management to keep patients safe and keep operations running well. Healthcare groups find and lower risks in medical devices and medical steps. They use advanced predictions made possible by Digital Twin technology to do this. This work changes how people handle quality management practices. It shows that digital tools help healthcare run better and improve patient health. This study shows why healthcare must use new data methods for quality checks. These tools help make healthcare more reliable and safe for everyone who needs care.

This paper examines the integration of SAP Quality Management (QM) systems and machine learning (ML) for predictive quality management in modern industrial environments. It highlights how SAP QM enables real-time quality control, while ML techniques analyze large datasets to identify patterns and predict potential defects. The review synthesizes existing literature to identify key themes such as transformation of quality assurance models, implementation challenges, and the need for interdisciplinary collaboration. Despite notable advancements, gaps remain in model standardization, user feedback integration, and organizational readiness. The study also discusses the evolving role of predictive quality management within the context of Industry 4.0 and digital transformation. Finally, a conceptual framework is proposed to guide future research and practical implementation in enhancing product quality and operational efficiency.

Tam Zamanında Üretim (TZÜ) sistemi ilk kez Japonya'da Toyota firmasında uygulanmıştır. Bu sisteminin imalat firmaları arasında gittikçe tercih edilmesi, israfa duyarlı olması ve maliyetleri azaltma çabası içinde olması dolayısıyladır. Bu çalışmada, TZÜ'de tedarikçi ilişkisi konusu ele alınmıştır. Elektrikli ev aletleri üreten ve TZÜ yapısına uygun üretim yapan bir firma tespit edilerek tedarikçi ilişkileri değerlendirilmiştir. Seçilen bir ürün için daha önce 83 olan tedarikçi firma sayısı 19'a indirgenebilmiştir. Ayrıca, bu ürün için en iyi üretim parti büyüklüğü hesaplanarak, ürünün bileşen parça ihtiyaçları buna göre belirlenmiştir. Bunun sonucunda yıllık stok taşıma maliyetinde önemli bir düşüş sağlanabileceği tespit edilmiştir.

The study on assembly line balancing theory and concept, focusing on the textile sector in Karachi, Pakistan, specifically the stitching department of a company, aimed to enhance efficiency through meticulous analysis and optimization. By employing time and motion analysis techniques, the research sought to identify and eliminate redundant activities, ensuring a seamless workflow with minimal idle time. The methodology employed involved a comprehensive observation of the entire production process, starting from stitching through to packing. This involved using a stopwatch to meticulously analyze each step of the process, thus gaining insight into the current operational dynamics of the assembly line. Line balancing was ensured by calculating Standard Allowed

Several papers have discussed the importance of the Last Planner Method as a means of stabilizing the production process in building sites. After process stabilization, however, a continuous effort is necessary in order to maintain and perfect the positive results obtained from the implementation of production planning and control systems. This article presents the preliminary results from an ongoing research project undertaken in a construction company from the South of Brazil. The main objective of this investigation is to propose guidelines to maintain and improve production planning and control systems after process stabilization. A series of fifteen projects were studied, aiming to identify the main barriers and also factors that contribute to the success of planning and control systems in the long term. The main sources of evidence used were the PPC (Percentage of Plans Completed) indicator, causes of the non-completion of work packages and interviews with company directors, clients and site engineers. One of the major factors that contributed to the success of planning and control system was the realization of weekly meetings focussed on learning rather than problem solving. This meeting involves company directors, a planning and control coordinator, and all site engineers. The results achieved in different sites are periodically disseminated throughout the company, pointing out the main barriers for implementation. Also, a strong emphasis is given in those meetings to the discussion of the Last Planner Method underlying ideas.

In open pit mining, the most significant challenge is determining the optimum long-term production schedules that maximize the project value by providing ore to the processing plant at full capacity while satisfying all required constraints. For oil sands strategic mine planning and waste management, as mining advances in a specified direction, in-pit tailingscells' dyke footprints are released for dyke construction. The dykes are constructed from overburden, interburden and tailings coarse sands dyke materials which come from the mining operation. The construction of in-pit (and ex-pit) tailings impoundment dykes therefore needs to be well integrated with the waste management strategy to ensure regulatory compliance and sustainable mining. In this research, an uncertainty-based mathematical programming framework is developed based on mixed integer linear goal programming (MILGP) model for oil sands production scheduling and waste management. The effect of grade uncertainty on production schedules is investigated. The grade uncertainty financial risk associated with a production schedule is minimized using kriged estimates with a variance penalty scheme. This investigation is based on the concept of mean-variance analysis, which is the process of weighing variance (risk) against the expected net present value (NPV). Subsequently, the impact of organic rich solids (ORS) content on bitumen recovery during processing is also studied. ORS content is used to predict ore processability in addition to the traditional use of bitumen and fines contents, and its impact on NPV quantified. The developed MILGP model is implemented using new robust automated production targeting (APT) constraints that optimize the annual capacities for material mined and processed over the mine life. In addition, mining-cells are deployed for the generation of in-pit tailings-cells designs used as dedicated disposal areas for backfilling. Two main waste management approaches are used to implement the developed model. Implementation A; where the ultimate pit is divided into predetermined pushbacks as tailings-cells within the ultimate pit limit (UPL), and Implementation B; where the ultimate pit is divided into mining-cells that are used to generate in-pit tailings-cells designs. To verify the research models, three oil sands case studies were carried out. iv The first case study investigates the effect of grade uncertainty on production schedules. The technique applied is based on the concept of mean-variance analysis, which is the process of weighing risk (variance) against expected NPV. The model generates a range of NPV which represents the mining investment risk profile associated with grade uncertainty. The second case study explores the impact of ORS content on oil sands ore processability. The results showed a 3.46% overestimation of NPV arising from not taking into account the effect of ORS content on bitumen recovery during mine planning. The final case study examines the implementation of waste management strategies based on different size and number of unit mining-cells used in creating tailings-cells for backfilling. The results showed that, decreasing the volume of unit mining-cells used in creating the in-pit tailings-cells increases the NPV of the operation due to increased operational flexibility. Additionally, as the percentage of in-pit volume to be backfilled increases, more savings is generated from not sending tailings to external facilities at a higher cost. These results proved that the uncertainty-based MILGP model is a robust tool for optimizing oil sands long-term production schedules whilst taking into account grade uncertainty, ore processability and tailings-cells designs. Oil sands mine planning, waste management, mixed integer linear goal programming, grade uncertainty, kriged estimates, organic rich solids, mathematical programming, backfilling schedule, tailings-cells, automated production targeting. vi Finally, I would like to thank my lovely late parents, Ramadan and Arosia, who passed away during my research and were always looking forward to my graduation. May Allah cover them with his mercy, and I hope I have made them proud.

Research has shown that 57% of activities in a construction project is non-value adding (waste) which contributes to the poor performance of the sector. While other countries of the world such the USA, UK, Brazil, Nigeria and Israel among others are seeking to understand this challenge and deploy innovative ways and modern techniques to improve it, limited studies have explored factors that contribute to non-value adding activities (NVA) in the Gibraltar construction industry. The current study aims to identify the factors that contribute to NVA on construction sites in Gibraltar and to present an outlook on how this could be minimised using Last Planner System(LPS). A combination of quantative and qualitative research approaches were used. Thirtyone questionnaire responses were analysed and seven semi-structured interviews were conducted. The investigation reveals that the development of unrealistic schedules, lack of adequate training, delayed approval process and work interruption due to the community are the key factors that contribute to NVA. The study found that the suggestions offered by construction professional for minimising NVA align with some LPS principles. The study concludes that some of the current practices, could serve as justification for the introduction of LPS in the construction sector of Gibraltar.

Businesses that want to compete globally and grow their operations must prioritize planning. This includes planning for production processes, sourcing materials, labor availability, and quality control. Planning product capacity is essential for small and medium-sized enterprises (MSMEs) because it impacts their costs and profits. However, limited capital can make this challenging. Businesses can use aggregate planning to optimize their operations to address this issue. In this study, we analyzed the application of product capacity through aggregate planning at the Cijoged Subang Plain T-shirt Convection. We used the Smooth Production method and POM QM for Windows software to collect and process data. Our findings suggest that implementing aggregate planning can help businesses map their costs and meet product demand capacity, including expenses related to regular and overtime working hours, subcontracting, and inventory.

In a previous paper, Alattas, Grossmann & Palou--Rivera ( ) developed a single--period, nonlinear programing refinery planning model using the fractionation index (FI) for the crude distillation unit (CDU) equations. In this paper, the single period model is modified to a mixed--integer nonlinear programming (MINLP) model to determine the sequencing, changeovers and processing times of crude oils over multiple time periods. The MINLP equations include traveling salesman problem constraints to generate the crude oil sequences that maximize profit. Moreover, the disjunction for the fractionation index (FI) is formulated with mixed integer constraints as opposed to the Heaviside function formulation of the previous work. The resulting model is shown to be robust and relatively fast. When subcycles arise, they are eliminated by adding appropriate subtour elimination constraints. Examples with up to 5 crude oils and 6 weeks time horizon are presented to illustrate the application of the proposed model.

Contemporary manufacturing companies are navigating industrial digitalization anticipating increased production efficiency and competitiveness in a volatile environment. This study focuses on the implementation processes of digital tools for production planning and control (PPC), i.e., advanced planning and scheduling (APS) software, in relation to the application of analog planning with physical flow boards. Digital tools can support understanding the consequences of production changes and variations, hence facilitating adaptable and resilient manufacturing. However, technological changes can be daunting, and effective implementations require dynamic capabilities to remain competitive in elusive environments. The aim is to study the implementation processes of an APS software to understand the requirements of fruitfully moving from analog planning to next-generation digital tools for decision support in PPC. The paper presents an explorative case study, at a manufacturing company w...

The Process Specification Language (PSL) [6] is a first-order logical theory designed to describe manufacturing or business processes and formalize reasoning about them. It has been developed by several authors over a period of years, yet it is inconsistent with the simplest axioms that preclude non-trivial models. We demonstrate several inconsistencies using an automated theorem prover and attempt to repair the inconsistencies. We conclude that even with our amendments, PSL with its infinite models remains inadequate to represent complex industrial processes. We propose an alternative axiomatization that admits finite models, which may be better suited to automated theorem provers and model finders than the current version of PSL.

This study focuses on the design, development, and evaluation of an integrated Design and Implementation of a Brokerage Selling and Rental Management Portal aimed at enhancing operational efficiency and customer satisfaction in the real estate sector. Traditional real estate brokerage and property management processes involve numerous manual tasks, including documenting transactions, managing property listings, and ensuring legal compliance, which can lead to inefficiencies, delays, and potential errors. Recognizing these challenges, the study proposed a unified portal that consolidates both brokerage selling and rental management functionalities into a single, user-friendly platform. The system allows users to create, read, update, and delete (CRUD) functionalities broker, agent, and property information, thereby centralizing essential data for streamlined access and improved transaction oversight. The development process employed the Rapid Application Development (RAD) methodology, characterized by iterative prototype cycles, rapid testing, and continuous refinement based on feedback from administrators and IT experts. This approach enabled the researchers to design a system aligned with end-user needs, ensuring that functional requirements were effectively met. System quality was evaluated using the ISO/IEC 25010:2023 software quality framework, focusing on attributes such as Functional Suitability, Performance Efficiency, Compatibility, Reliability, and Security. Results demonstrated very satisfactory to excellent scores across all metrics, with a total mean of 4.96, reflecting strong performance, dependability, and secure handling of data. In addition, usability was assessed using the USE Questionnaire, which measures Usefulness, Ease of Use, Ease of Learning, and User Satisfaction. The portal achieved a perfect mean score of 5.00 in all categories, indicating that users strongly agreed with its ease of operation and overall usefulness.

Artificial Intelligence deployment in enterprise environments has accelerated dramatically, yet governance frameworks struggle to keep pace with the technology's rapid evolution. This research develops a comprehensive risk and compliance framework specifically designed for responsible AI governance in enterprise systems. The study addresses critical gaps where organizations implement AI solutions without adequate oversight mechanisms, creating substantial regulatory, ethical, and operational risks. Through analysis of existing governance models and emerging regulatory requirements, we propose a multi-layered framework that integrates risk assessment, compliance monitoring, and ethical oversight into enterprise AI operations. The framework emphasizes practical implementation within existing corporate governance structures rather than creating parallel oversight systems. Our approach balances innovation enablement with appropriate controls, recognizing that overly restrictive governance inhibits beneficial AI adoption while insufficient oversight creates unacceptable risks. The research demonstrates how enterprises can establish systematic governance processes that ensure AI systems operate responsibly, comply with evolving regulations, and align with organizational values. This work contributes both theoretical frameworks for understanding AI governance challenges and actionable guidance for implementing effective oversight in diverse enterprise contexts.

• This paper examines two late archaic black-figure vases, presenting new insights into the dynamics of ceramic production and cultural exchange in pre-Roman Italy. The first vase from Garaguso (Lucania) depicts an offering scene, a theme closely tied to Campanian ritual imagery. Despite its fragmentary state, the vase's thematic and stylistic features suggest a Campanian origin, though a local workshop cannot be excluded. The second vase, a cup-skyphos in the Dresden Antikensammlung, was originally attributed to Boeotian production. A re-evaluation, considering formal and stylistic parallels, supports a reattribution to a Campanian workshop of the early 5th century BCE. These two vases enrich the corpus of Campanian pottery within the framework of interactions between Greek, Etruscan, and Italic cultures in southern Italy and highlight the challenges of ceramic attribution in a cross-cultural landscape.

In this work two novel image processing techniques are applied to detect and delineate complex salt bodies from seismic exploration profiles: Hough transform and principal component analysis (PCA). It is well recognized by the geophysical community that the lack of resolution and poor structural identification in seismic data recorded at sub-salt plays represent severe technical and economical problems. Under such circumstances, seismic interpretation based only on the human-eye is inaccurate. Additionally, petroleum field development decisions and production planning depend on good-quality seismic images that generally are not feasible in salt tectonics areas. In spite of this, morphological erosion, region growing and, especially, a generalization of the Hough transform (closely related to the Radon transform) are applied to build parabolic shapes that are useful in the idealization and recognition of salt domes from 2D seismic profiles. In a similar way, PCA is also used to identify shapes associated with complex salt bodies in seismic profiles extracted from 3D seismic data. To show the validity of the new set of seismic results, comparisons between both image processing techniques are exhibited. It is remarkable that the main contribution of this work is oriented in providing the seismic interpreters with new semi-automatic computational tools. The novel image processing approaches presented here may be helpful in the identification of diapirs and other complex geological features from seismic images. Conceivably, in the near future, a new branch of seismic attributes could be recognized by geoscientists and engineers based on the encouraging results reported here.

Production planning is a complex problem that is typically decomposed into decisions carried out at different control levels. The various methods used for production planning often assume a static environment, therefore, the plans developed may not be feasible when shop floor events change dynamically. In such an operating environment, a system simulation model updated with real-time data can be used to validate a proposed plan. In this paper, we propose a framework to evaluate and validate the feasibility of high-level production plans using a simulation model at a lower level thereby providing a base for improving the upper level plan. The idea is demonstrated with an assembly plant where the aggregate plan is evaluated using discrete event simulation (DES) of shop floor operations with resources allocated according to constraints imposed by the aggregate plan. We also discuss standardized integration interfaces required between simulations and production planning tools.

Supply chain disruptions have intensified dramatically in recent years, exposing critical vulnerabilities in traditional procurement and production planning systems. Organizations increasingly recognize that isolated, siloed enterprise resource planning modules cannot adequately respond to volatile demand patterns, supplier uncertainties, and operational complexities. This research examines how integrated synchronization between SAP Production Planning (PP) and Procurement modules enhances supply chain resilience through improved visibility, coordinated decision-making, and adaptive responses to disruptions. Through a mixed-methods study involving implementation analysis at five manufacturing organizations and quantitative assessment of key performance indicators over 18 months, this research demonstrates that integrated SAP PP-Procurement synchronization reduces stockout incidents by 42%, decreases emergency procurement costs by 38%, and improves on-time delivery performance by 31% compared to traditional siloed approaches. The study develops a comprehensive integration framework encompassing master data harmonization, real-time information exchange, collaborative planning processes, and exception management protocols. Findings reveal that successful integration requires not only technical configuration but also organizational change management, cross-functional collaboration, and continuous process refinement. The research identifies critical success factors including executive sponsorship, clear data governance, standardized workflows, and balanced automation with human oversight. This work contributes both a validated integration methodology for SAP PP-Procurement synchronization and empirical evidence of its impact on supply chain resilience, providing practical guidance for organizations seeking to strengthen their operational capabilities against disruptions.

Supply chains (SCs) are increasingly challenged to deliver greater value with fewer resources while minimising environmental impact. Postponement strategies have emerged as a potential solution to strike this balance, yet their impact on environmental sustainability beyond economic considerations remains under-examined. Recognising this gap, this study reports on a systematic literature review that employs a design-oriented approach combined with the Contexts, Interventions, Mechanisms, and Outcomes (CIMO) logic to deepen the understanding of the effects of postponement strategies on environmental and economic sustainability. The study elaborates on the extant literature to offer a nuanced conceptualisation of postponement and capture its recent evolution, extending its scope beyond deferring value-adding activities that increase uncertainty to also include the activities' geographical location and acknowledge the involvement of different SC partners. This further enabled the precise characterisation of contemporary postponement applications, leading to the development of propositions that suggest under which conditions postponement strategies may enhance or harm both the environmental and economic performances of SCs. Finally, building on the identified findings and propositions, a future research agenda is provided to encourage further advancements in postponement and contribute to more sustainable SCs.

Enterprise Resource Planning (ERP) systems were originally designed to ensure transactional consistency through predefined item-based structures [4][5]. In platforms such as Oracle E-Business Suite (EBS) R12 Order Management, sales orders require explicit commitment to specific stock keeping units (SKUs) at the time of order entry [1]. While this approach preserves data integrity and financial accuracy, it limits flexibility in industries where customers express demand through functional attributes rather than exact item numbers. This paper presents a functional framework that enables attribute-based order capture and dynamic fulfillment determination within Oracle EBS R12. The proposed approach leverages standard inventory categorization and Available-to-Promise (ATP) evaluation mechanisms [2][3] to identify eligible items that satisfy customer-defined specifications. By deferring final SKU commitment until availability is assessed, the framework introduces flexibility at the customer interaction stage while preserving downstream Order-to-Cash integrity [1]. The solution demonstrates how structured functional design can reconcile specification-driven demand with rigid ERP architectures, offering a scalable and reusable model for enterprises managing interchangeable or commoditybased products.

A multi-period planning model for underground cut-and-fill operations was constructed for the purpose of maximizing discounted profit under given production constraints. The ore grades were estimated through geostatistics for minimizing the estimation errors, and production costs were calculated on the basis of the practical operation data. A sequential planning algorithm based on dynamic programming (DP) was then developed to specify the most profitable mining sequence, and applied to a Chinese copper-iron mine employing cut-and-fill stoping. Calculation results showed that the proposed DP-based sequential planning strategy can produce larger discounted profits than those obtained by the advance and retreat mining sequences.

Plastic recycling has the exciting advantage of having a low impact on global warming and environmental toxicity, as well as a high impact on waste reduction and environmental sustainability. The process can be classified into four categories namely; primary recycling, secondary recycling or mechanical recycling, tertiary recycling, and quaternary recycling or incineration. When conducted properly, it has the potential for not only maintaining a circular plastic economy but also improving the profitability of the enterprise. This paper presents preliminary procedural investigations on Z Company's typical plastic recycling organization. Using a case study analytical procedure, the pertinent recycling plant parameters were elucidated. Issues with the existing layout and methods of the plant were highlighted. A careful examination of the production planning revealed great potential for improvement of the profitability of the enterprise. The result shows that the application of appropriate process optimization techniques can result in improving the fault lines evident in the existing system.

This paper analyses the issue of ensuring enhanced productivity and robustness to work schedules designed for multi-operational batch production processes, when a fixed, limited number of workstations can be used for production. The productivity of a batch production schedule for a specific quantity of items is measured by the length of its cycle time, while the robustness of the schedule is given by the size and distribution of operational slack times that are ensured during the production process run. It is mathematically demonstrated that a simple process planning solution may be the key for meeting the above mentioned objectives, if it is possible to be applied in practice in combination with the lot streaming strategy for the production flow.

Construction needs a unified productivity method. This paper asserts one. Shewhart's Plan-Do-Check-Act (PDCA) was created for the manufacturing industry. It has been helpful for construction contractors as a starting point. Still, it contains misalignments and blind spots, making it suboptimal, i.e., not readily adaptable to a custom installation and rehabilitation industry. This paper explores the problems of the model and provides a potential solution that evolves Shewhart's model. First, we describe the realities that for-profit construction organisations face, and then we expand and tailor PDCA to meet those issues. In summary, completed tasks comprise a finished project. Each project requires dozens of physical installation activities. As an improvement, a repetitive set of management activities that support trade professionals' on-site tasks, done on time and ultimately, will deliver safety, quality, cost and schedule. This paper examines possible project input variations and projected results. This approach applies to new construction and rehabilitation projects and can be used as a diagnostic tool in post-job reviews to prompt continuous improvement.

This study investigates the utilisation of Integer Linear Programming (ILP) to enhance workforce scheduling at the ABInBev (International Breweries Port Harcourt) Logistics Facility, characterised by high demand and heavy shift labour. In these situations, traditional manual scheduling methods typically cause problems including wasted labour, tired employees, irregular shift coverage, and higher operating costs. To solve these problems, a 0-1 ILP model was designed to find the best way to allocate personnel to shifts while still meeting operational, regulatory, and fatigue-related needs. The model takes into account the availability of workers, the demand for shifts, the skills needed, and labour laws to come up with the best timetable. Results, based on realistic operational assumptions, show that workforce utilisation will go up by 15-20%, labour expenses will go down by 12-18%, and fatigue-related workload concentration will go down by 25-30%. Operations will also be more responsive. The results show that ILP is a strong, data-driven way to schedule workers and can help make brewery and fastmoving consumer goods logistics operations in Nigeria more efficient, safe, and resilient.

Achieving production targets is the goal of all companies, especially manufacturing companies. PT Ganding Toolsindo is an automotive component manufacturing company that aims to provide a high level of service and is committed to its clients, so achieving production targets is essential. However, it is unfortunate that there are still problems regarding the non-fulfillment of production targets. In addition, issues regarding rusty raw materials and waste also occur there. The cause of this problem is the advantages and disadvantages of raw materials because production planning and control have not been appropriately implemented. Therefore, this Community Service (PkM) aims to assist partners in solving these problems through training, production planning, and control assistance. The PkM series is carried out with a preliminary survey, material preparation, training, and mentoring. The material given in this PkM activity is about "Introduction to Production Planning and Control&...

Satisfying customer demand at an optimal cost is the most important concern for the high-level management of every company. This dissertation details i) the development of a strategic/tactical model for the distribution of production responsibilities to different sites/factories and ii) the design of an inter-area logistics flow ensuring demand satisfaction, by consider the production capabilities of each site, while minimizing the total costs of production output. A mixed integer program, which includes the supply of raw materials and the distribution of finished products in the respective markets, was proposed to manage this production problem. This concept encompassed two case studies: the first involved a scenario in which setup costs were identical (Case 1); the second entailed setup costs that differed from product to product (Case 2) to determine the optimal costs by understanding the role of the setup costs. This model also simultaneously automatically assigns a production job to a particular factory and transports the finished goods among the sites, if the production costs at those sites are relatively higher than the transportation costs. CPLEX solver, used for the numerical analysis, determined that this proposed formulation could indeed manage such a complex problem. These experiments were also used to predict the role of Fixed and Setup costs on the percentage of products transferred among the companies for purposes of satisfying the demand.

Satisfying customer demand at an optimal cost is the most important concern for the high-level management of every company. This dissertation details i) the development of a strategic/tactical model for the distribution of production responsibilities to different sites/factories and ii) the design of an inter-area logistics flow ensuring demand satisfaction, by consider the production capabilities of each site, while minimizing the total costs of production output. A mixed integer program, which includes the supply of raw materials and the distribution of finished products in the respective markets, was proposed to manage this production problem. This concept encompassed two case studies: the first involved a scenario in which setup costs were identical (Case 1); the second entailed setup costs that differed from product to product (Case 2) to determine the optimal costs by understanding the role of the setup costs. This model also simultaneously automatically assigns a production job to a particular factory and transports the finished goods among the sites, if the production costs at those sites are relatively higher than the transportation costs. CPLEX solver, used for the numerical analysis, determined that this proposed formulation could indeed manage such a complex problem. These experiments were also used to predict the role of Fixed and Setup costs on the percentage of products transferred among the companies for purposes of satisfying the demand.

Background. Revealing tacit knowledge often is seen as very valuable for organizations, although it is usually challenging to enunciate and share this type of knowledge. Methods. This study uses a participatory design and the application of a board gaming simulation as instruments to extract tacit knowledge. To illustrate this application, the gaming simulation is played with entrepreneurs from horticulture. Horticulture represents a complex social system where tacit knowledge plays a major role in the trade process. A participatory design process is used to explore whether the design and play of gaming simulations enable participants to explicate their tacit knowledge. Participants’ participation in designing the gaming simulation explicated that reconstructing reality was a prerequisite for their commitment. Results. The results from playing simulation sessions show that participants were able to: (1) narrow down the anecdotic behaviour to a few factors; (2) to structure these fac...

Background/Objectives: Nowadays, the usage of Android mobile is increasing day by day. In this paper a new application is proposed called Tracking Theft Mobile Application (TTM) to identify the theft mobile. Methods/Statistical Analysis: TTM app is developed in Android platform. The usage of TTM App is that it will send the automatic message, current location of theft mobile phone and automatic captured image of the person who had stolen our mobile phone to the contact number which already registered in TTM app when installing it in user's mobile. Findings: Android has been recommended for the developers because of its simplicity in working. Our new proposed App is a Tracking Theft Mobile (TTM). Can find our mobile phone without the help of the police or higher officials. Can find the correct person by receiving his image. Can locate the person by receiving the message as well as location details. Application/Improvements: Comparing to existing method the accuracy is improved in...

A key to designing the effective computer-based decision support system is deciding which models best support the decision makers. Since most decision support systems include optimizing rater than tracking models, this experiment examines the evidence for tracking when making a production scheduling decision. The experiment found evidence that tracking behavior was occurring. This suggests the need to support tracking behavior with decision support systems. Approaches to such support are offered.

This paper addresses the multi-product, multi-period capacitated lot sizing problem. In particular, this work determines the optimal lot size allowing for shortages (imposed by budget restrictions), but with a penalty cost. The developed models are well suited to the usually rather inflexible production resources found in retail industries. Two models are proposed based on mixed-integer formulations: (i) one that allows shortage and (ii) one that forces fulfilling the demand. Both models are implemented over test instances and a case study of a real industry. By investigating the properties of the obtained solutions, we can determine whether the shortage allowance will benefit the company. The experimental results indicate that, for the test instances, the fact of allowing shortages produces savings up to 17% in comparison with the model without shortages, whereas concerning the current situation of the company, these savings represent 33% of the total costs while preserving the rev...

Production planning is very necessary in a business process that aims to minimize the total cost of production. In this research, automation of production planning using data based on the Islamic boarding school business processes. This research uses descriptive research which aims to obtain information in the implementation of the business process planning of Islamic boarding school. The calculation of production costs in this study was carried out in Microsoft Excel by determining the total targets and raw materials of the Islamic boarding school business process, then calculating the production costs of the Islamic boarding school process until finding the optimal production costs for each student for 3 years. - The year of study is Rp. 1,242,542 rupiah / Islamic student for a total of 300 Islamic students.