Production Lot Size Research Articles

Effect of Strategic Inventory Management on Performance of Small-Scale Manufacturing Firms in Lagos State, Nigeria

The aim of the study is to investigate the effect of Strategic Inventory Management on the Performance of Small-scale Manufacturing Firms. The study used primary data to obtained necessary information from the firms. The population size includes 31 Small-Scale manufacturing firms situated in Ikeja, Lagos State, Nigeria. A simple random technique was used to select 220 respondents from the departments of Production, Marketing and Administration.Data on variables such as Inventory Management tools, Strategic decision policy and performance variables were sourced from the respondents with the questionnaire, and analyzed using descriptive and inferential statistics.The study showed that Strategic Inventory Management influences better performance of the small scale manufacturing firm if appropriately used. Inventory management tools like the ABC system, Two-way bins, EOQ, Production Lot Size and Quantity discount Model should form the bedrock of their inventory management practices. The study concluded that inventory management facilities should be provided by small scale manufacturing firms to support their performance technically which will bring about improved performance.

A single-vendor multi-buyer production remanufacturing inventory system under a centralized consignment arrangement

The reuse/remanufacturing of economically viable used products that are collected from the end customer has emerged as an inherent part of many supply chain operations due primarily to increased customers awareness and recent environmental protection legislations. This paper considers the environmentally friendly approach of remanufacturing, in the context of a two stage closed loop supply chain comprised of a single vendor and multi buyers where all parties involved operate under a centralized consignment stock agreement. We first develop a mathematical model for this production remanufacturing inventory system and then carry out a thorough model analysis leading to the proof of global optimality of the solutions. We further illustrate the model using several numerical examples followed by a sensitivity analysis that seeks to investigate the impact of key model parameters on the optimal solutions. The obtained results indicate that as the vendor’s setup cost increases relative to the buyers’ ordering cost, the system opts for producing larger lots per setup since this better complies with the economies of scale. The percentage of returned items as well as the holding costs are also found to be key parameters greatly impacting the production lot sizing and the shipping policy of the end item to the downstream buyers.

A vendor-buyer inventory model for defective items with errors in inspection, stochastic lead time and freight cost

This study develops a mathematical model for an integrated vendor-buyer inventory with defective items and inspection error. We assume an imperfect production process with a known of defective probability. The buyer conducts a 100% quality check. However, due to an imperfect inspection process, the quality-controller may reject a good item as a defective item (Type I error), or accept a defective item as a non-defective item (Type II error). Different from existing research, we incorporate freight cost (a function of shipping weight and the distance between the vendor and the buyer) and stochastic lead time (a function of production and transportation times). The objective of the study is to minimize the joint total expected cost. This study indicates that Type I error is more significant when it is compared with Type II error. We also illustrate how the joint total expected cost and the lead time are significantly influenced by the distance of the buyer and the vendor. The results of our analysis also show that lead time can be shortened if the vendors speed up their shipment with smaller production lot sizes. Numerical examples and sensitivity analysis are given to illustrate the results.

Comparison of msc-evs manufatured in 2D versus scalable 3D bioreactor systems

Background & Aim There have been over 800 registered clinical trials using mesenchymal stem/stromal cells (MSCs) for therapeutic applications. Due to their potential as a key bioactive agent in regenerative medicine applications, MSC-derived extracellular vesicles (MSC-EVs) are increasingly being investigated as a clinical therapy. It was recently found that the number of exosomes released from 2 million MSCs in 48 hours is equivalent to a single dose for a rodent (Phinney, Pittenger 2017). Hence, most indications would require an MSC production lot size that is hardly achievable in 2D planar cell culture; larger scalable bioreactor systems will be crucial to generate enough EVs for clinical doses. Therefore, this study compared the yield and characteristics of MSC-derived EVs generated in typical 2D culture with those from scalable 3D bioreactor systems. Methods, Results & Conclusion Human bone marrow-derived MSCs were cultured on microcarriers in 3L and 15L bioreactors. After initial cell inoculation, a bioreactor feed was added on Day 3, and cultures were switched to an EV collection media on Day 4, then cultured for 3 additional days. Samples of the conditioned media were analyzed for particle size and concentration. The collected MSC-EVs were evaluated for protein and RNA expression and wound healing capability. MSC-EVs were compared between bioreactor scales and with a 2D control cultured in a 10-layer cell stack. Higher cell densities were achieved in 3D compared to 2D culture, with similar cell densities in the 3L and 15L bioreactors. The conditioned media was analyzed after the 3-day EV collection period. Particle size distributions were similar across culture systems. The particle concentration in the conditioned media (particles/L media) was similar between the 3L and 15L bioreactors, with the 3D cultures about 3x higher than 2D culture. When particle concentration was normalized to cell number, the productivity (particles/cell) was comparable in the two bioreactor cultures, with 3D cultures greater than 2D. Optimizing EV yield will become increasingly important as EVs are used in the clinic. We have developed a scalable process for MSC-EV generation in a bioreactor. The comparison between 2D and bioreactor cultures demonstrates that a greater EV yield can be accomplished in 3D culture. We intend to continue to scale this process up to production scale (80L) bioreactors, which is critical to generating lot sizes for clinically relevant doses of MSC-EVs.

An eletricity inventory model for power plant and transmission stasion system with in-house demand and carbon emission cost

This paper develops a mathematical model for optimizing energy storage size for a single power plant and a single transmission station. The electricity generated by the power plant is transmitted to the transmission and distribution station and then consumed by the end-customers. Besides providing electricity to end customers, a power plant also supplies electricity to their utility system to satisfy the in-house demand. The proposed model considers in-house demand, end-costumer’s demand and carbon emissions. The carbon emission is calculated from production activities. The objective of the model is to determine the supply size of in-house demand, shipment size of end-costumer’s demand, production lot size factor and emergency backup factor to minimize a total cost incurred by a power plant and transmission station. We utilize an inventory theory to develop our model and propose an algorithm to obtain the optimal solution for this problem. A numerical example is provided to illustrate the application of model.

Lot size optimisation in two-stage manufacturer-supplier production under carbon management constraints

Carbon management of production planning involves multiple supply chain parties in different processes. This paper studies synergistic cooperation among supply chain parties for more effective emission reduction. Since a supply chain generally includes multiple parties, this paper focuses for simplicity on supplier, manufacturer and retailing. It studies a centralised make-to-order (MTO) production system involving a manufacturer and an internal supplier, with an objective to maximise the total profit by optimising the production lot sizes for the supplier and the manufacturer, who each operates a production line under MTO mode. The proposed model considers two carbon management scenarios of carbon cap and product sustainability under consumer green awareness, of which the impacts are deliberated with analytical solutions and numerical experiments. The result shows that the maximal profit can be achieved under carbon management constraints by adjusting the production lot size in both scenarios. Through sensitivity analysis, it is found that the carbon cap policy restricts the company profitability and that a high consumer green sensitivity can improve the profitability of green products. Therefore, the government and companies should cooperate to improve product sustainability and create greener markets. This paper contributes to the burgeoning field of carbon management in supply chain and provides theoretical guidance for adjusting production plans.

A collaborative EPQ inventory model for a three-echelon supply chain with multiple products considering the effect of marketing effort on demand

This paper presents an inventory model for a three-echelon supply chain with multiple products and multiple members considering the demand as an increasing function of the marketing effort. In the proposed inventory model, a collaborative approach is studied and an analytical method is applied to obtain the optimal production lot size and the optimal marketing effort in order to achieve the maximum profits. Some numerical examples are illustrated to justify the model. Moreover, a sensitivity analysis is well done in order to analysis the effect of the changes of key parameters of inventory model on the the maximum benefits of all members of the chain.

Joint optimisation of production, maintenance and quality for batch production system subject to varying operational conditions

This paper considers the integration problem of production, maintenance and quality for a capacitated lot-sizing production system subject to deterioration. The effects of varying operational conditions from batch to batch on system reliability and product quality are modelled by proportional hazards models, resulting in non-monotonic failure rate and defect rate. After each batch production, imperfect preventive maintenance (PM) is determined to mitigate the system deterioration, and inspection is taken to sort nonconforming items in the finished goods. Once the cumulative number of nonconforming items exceeds a predetermined threshold, an overhaul is performed to renew the system. An integrated model for optimising production plan, PM plan and overhaul strategy is developed to minimise the total cost while satisfying all product demands. A genetic algorithm is proposed to solve the integrated model efficiently. Numerical results validate the rationality of the model with varying operational conditions consideration and its applicability in economic benefits.

Two-echelon supply chain coordination with advertising-driven demand under Stackelberg game policy

This paper develops a two-echelon supply chain model with a single manufacturer and a single retailer, where the demand is sensitive to advertising and retail price. To resolve the supply chain coordination, three strategies are introduced as retailer leader-manufacturer follower, manufacturer leader-retailer follower, and centralised supply chain. Based on these strategies, this paper suggests an optimal production rate, a production lot size, shortage level, an advertising expenditure, and retail price. Stackelberg approach is employed for solving leader-follower game to obtain the maximum profit of both manufacturer and retailer. The improved algorithm is developed to obtain the numerical results. For testing the model, this paper considers several numerical experiments, graphical illustrations, and sensitivity analysis. The result shows that the strategy of retailer leader-manufacturer follower obtains the highest profit than other strategies. [Received: 23 September 2017; Revised: 28 November 2017; Revised: 29 April 2018; Revised: 19 July 2018; Revised: 21 October 2018; Accepted: 21 October 2018]

The effect of purchasing strategy on the economic production quantity model subject to random machine breakdown

In this article, we develop an economic production quantity (EPQ) model subject to process deterioration, machine breakdown and two types of repair, and study the influence of purchasing strategy on the system's expected total cost, as an alternative option to holding safety stock. It is obvious that the shortages may occur due to the prolonged repair time. To avoid this issue, we assume that the manufacturer could purchase some quantities from an available supplier with fixed non-zero lead-time. This paper addresses the following question: how much production lot size and purchasing lot size are required to minimise the expected total cost? The model is developed under general machine breakdown and repairs time distributions. The optimality of the model under exponential failure and exponential repair times are studied. For the numerical example, we illustrate the outcome of the proposed model and perform a sensitivity analysis on parameters, which directly influence optimal decisions.

Two-echelon supply chain coordination with advertising-driven demand under Stackelberg game policy

This paper develops a two-echelon supply chain model with a single manufacturer and a single retailer, where the demand is sensitive to advertising and retail price. To resolve the supply chain coordination, three strategies are introduced as retailer leader-manufacturer follower, manufacturer leader-retailer follower, and centralised supply chain. Based on these strategies, this paper suggests an optimal production rate, a production lot size, shortage level, an advertising expenditure, and retail price. Stackelberg approach is employed for solving leader-follower game to obtain the maximum profit of both manufacturer and retailer. The improved algorithm is developed to obtain the numerical results. For testing the model, this paper considers several numerical experiments, graphical illustrations, and sensitivity analysis. The result shows that the strategy of retailer leader-manufacturer follower obtains the highest profit than other strategies. [Received: 23 September 2017; Revised: 28 November 2017; Revised: 29 April 2018; Revised: 19 July 2018; Revised: 21 October 2018; Accepted: 21 October 2018]

TU Wien Pilot Factory Industry 4.0

Abstract Driven by present megatrends like digitization and demographic change, Learning Factories all over the world are gaining recognition in science, industry and society. In these collaborative learning environments, students and interested trainees from industry acquire methodological, social and personal competencies for future challenges in production. TU Wien Pilot Factory Industry 4.0 (in short TU PF) is a Pilot, Demonstration and Learning Factory, aiming to provide companies a fundamental insight into Industry 4.0 techniques, applications and associated challenges through exemplary implementation of a digitized production environment as well as subsequent research, workshops and presentations. Thereby a focus is set on information and communication technologies (ICT) particularly, to realize the production of customer-specific products in small lot sizes. In contrast to other Learning Factories, TU PF emphasizes not only on teaching knowledge, but also on the demonstration of novel production concepts as well as the development, implementation and evaluation of prototypes together with industry partners. This paper gives an insight into the current status of TU PF and its consistent information flow from engineering to production.

Developed priority rules support system for ELSP: a case study

Economic lot size scheduling problem (ELSP) is one of the most challenging problems in production and operation management. Although studied extensively in the literature, yet it is still one of the major topics in scheduling research. ELSP with its various configurations can be found in many industrial fields. In this paper, a producer of fast moving consumer goods (FMCG) is considering this decision. The company has a production line producing a range of products having dependent changeover cost. It is required to determine the production schedule and lot size that minimise the total cost. A new heuristic model is developed that uses different priority rules to find the best lot size that minimises the total cost. The new model is then simulated to analyse and compare the performance for the different rules with different lot size. The results of the case study used show that choosing the scheduling policy relies on a suggested cost ratio threshold which is a function of the cost parameters of the operation. The effect of different cost parameters on the performance of different priority rules is also discussed.

Developed priority rules support system for ELSP: a case study

Economic lot size scheduling problem (ELSP) is one of the most challenging problems in production and operation management. Although studied extensively in the literature, yet it is still one of the major topics in scheduling research. ELSP with its various configurations can be found in many industrial fields. In this paper, a producer of fast moving consumer goods (FMCG) is considering this decision. The company has a production line producing a range of products having dependent changeover cost. It is required to determine the production schedule and lot size that minimise the total cost. A new heuristic model is developed that uses different priority rules to find the best lot size that minimises the total cost. The new model is then simulated to analyse and compare the performance for the different rules with different lot size. The results of the case study used show that choosing the scheduling policy relies on a suggested cost ratio threshold which is a function of the cost parameters of the operation. The effect of different cost parameters on the performance of different priority rules is also discussed.

Imperfect production system with rework of regular production with sales returns by customers and buffer stock

Jamal et al. (2004) proposed a model, which dealt with the optimum batch quantity in a single-stage system in which rework is done by addressing two different operational policies to minimise the total system cost but their models do not considered sales return by customers. A portion of defective items produced are not successfully screened out internally during the production process and passed on to customers, thereby causing defect sales returns and reverse logistic from customers back to the manufacturer. In this direction, this paper develops an economic production quantity inventory model with sales return by customers for determining the economic production quantity for a single product, which is manufactured in a single-stage manufacturing system that generates imperfect quality products and all these defective products are reworked in the same cycle. Mathematical model is developed and the optimal production lot size which minimises the total cost is derived.

Methodical approach for the development of a platform for the configuration and operation of turnkey production systems

Shorter product lifecycles lead not only to faster time-to-market for products but also to the need for just as fast available associated production systems. These shorter product lifecycles, as well as the increasing individualization of products, also result in further decreasing production lot sizes. Young companies in China in particular are characterized by a very high speed of innovation but may not have the necessary manufacturing knowledge or capacities to bring their developed products to the market with a scalable production. For this reason, there is a great need to quickly set up and commission turnkey production systems or to reconfigure existing production systems for new production tasks in the shortest possible time. This paper describes the design and architecture of a cloud platform with the aim to support a manufacturer independent design process for turnkey production systems. This process ranges from the product to be manufactured to the operation of the production system. Firstly, the structure and methodology used to link the various objectives are discussed. The system for recording and structuring product and production system data to create reusable modules from components and machines is described. Subsequently, the use of standardized modules is developed to support reconfiguration of the production system during operation. In addition, the digital business models tailored to the production system are proposed to the platform user for commissioning and operation of the plant. A case study is conducted to validate the proposed methodology.

Integrated vendor-buyer inventory model in a supply chain with variable lead time and setup cost reduction

The single vendor single-buyer integrated production inventory system has been an object of study for a long time but little is known about the effect of investing in reducing setup cost on the integrated inventory models with variable lead time and production lot size dependent lead time and transportation time. A mathematical model is derived to investigate the effects of setup cost reduction on the integrated inventory system by reducing the total cost system. A numerical example is included to illustrate the results of the model. Finally, graphical representation is presented to illustrate the model. The solution procedure is furnished to determine the optimal solution and the sensitivity analysis has been carried out to illustrate the behaviours of the proposed model.

Effect of Energy and Failure Rate in a Multi-Item Smart Production System

To form a smart production system, the effect of energy and machines’ failure rate plays an important role. The main issue is to make a smart production system for complex products that the system may produce several defective items during a long-run production process with an unusual amount of energy consumption. The aim of the model is to obtain the optimum amount of smart lot, the production rate, and the failure rate under the effect of energy. This study contains a multi-item economic imperfect production lot size energy model considering a failure rate as a system design variable under a budget and a space constraint. The model assumes an inspection cost to ensure product’s quality under perfect energy consumption. Failure rate and smart production rate dependent development cost under energy consumption are considered, i.e., lower values of failure rate give higher values of development cost and vice versa under the effect of proper utilization of energy. The manufacturing system moves from in-control state to out-of-control state at a random time. The theory of nonlinear optimization (Kuhn–Tucker method) is employed to solve the model. There is a lemma to obtain the global optimal solution for the model. Two numerical examples, graphical representations, and sensitivity analysis of key parameters are given to illustrate the model.

Rolling Supply Chain Scheduling considering Suppliers, Production, and Delivery Lot-Size

Supply chain management and integration play a key factor in contemporary manufacturing concept. Companies seek to integrate itself within a cooperative and mutual benefiting supply chain. Supply chain scheduling, as an important aspect of supply chain management, highly emphasizes on minimizing stock costs and delivery costs. Most previous researches on supply chain scheduling problems assume make-to-order production, which includes delivery cost in lot-size. This practice simplifies the complexity of the problem. Instead, this research discusses make-to-contract production, where the supply chain has a rolling planning horizon that changes according to contracts. Within a planning horizon, two types of interval are defined. The first is frozen interval, in which the manufacturing decision cannot be changed. The second is free interval, where schedules can be adjusted depending on new contracts. This research aims to build a robust rolling supply management schedule to satisfy customers’ needs, by considering supplier, production, and delivery lot-size simultaneously. The objective is to effectively decide a combination of supplier, production, and delivery lot-size that minimizes total cost consisting of supplier cost, finish good stock cost, and delivery cost. Based on the concept, this study designs a problem-solving process that combines the methods of rolling planning horizon and genetic algorithm. Delivery size (DS), finish good stock (FS), and early delivery cost (ED) are the three methods applied; each will provide a guideline to produce a feasible solution. By further considering the fluctuations in practical needs and performing an overall evaluation, a robust and optimal supply chain scheduling plan can be decided, including the optimal lot-sizes of supplier, production, and delivery. In the effectiveness test which considers 3 types of customer demands and 11 types of company cost structures, the simulated data test results suggest that the proposed methods in this study have excellent performance.

Microbial safety of cellular therapeutics—lessons from over ten years’ experience in microbial safety of platelet concentrates

Bacterial safety of cellular preparations, including blood products and cellular therapeutics, presents ongoing challenges for physicians, manufacturers and regulators. Although there have been many new approaches to enhance the microbial safety of cellular products during the last decade, established methods for microbiological control still need to be fully adapted to the special circumstances of cellular preparations. The experience from transfusion medicine regarding microbial safety of blood components has demonstrated the variety of problems and risk factors for the development of new strategies for microbial safety. Special attention has been given to the prevention and detection of bacterial contamination of platelet concentrates. But so far, none of the targeted strategies for rapid detection or pathogen reduction have become routinely implemented worldwide, in part at least because development and requirements of new technologies and their implementation into the routine setting are a whole different problem. But factors including the short shelf life and nontraditional lot sizes for cellular and gene therapy products are driving the need for rapid microbiological methods. In conclusion, lessons from the microbial safety of platelet concentrates enable us to understand that the detection or reduction in bacteria represents a more difficult challenge in comparison with viruses. Recent regulatory changes demonstrate that we are getting closer to the goal of a shift from the traditional view of sterility evaluation (identify and inactivate anything and everything) to a new thinking about microbiological control.