Performance Guarantees and Optimal Purification Decisions for Engineered Proteins

The reduction of lead time in the product development process (PDP) is one of the main challenges faced by organizations operating in dynamic and competitive markets, such as the textile sector. In this context, the application of lean manufacturing principles has proven to be a promising strategy to eliminate waste and increase efficiency. This article aims to analyze the joint application of Value Stream Mapping (VSM) and the Gemba Kaizen (GK) method in a multi-project PDP of a textile industry in Santa Catarina, seeking to highlight how these practices can contribute to continuous improvement. Methodologically, the study adopts action research, conducted in two intervention cycles: the first focusing on waste identification through VSM, and the second on implementing improvements via GK. The results revealed the existence of excessive information inventories, rework, and inconsistencies in material and data flows, which directly impacted lead time. The application of lean practices resulted in a 63% reduction in the rework rate in printing and a decrease of two days in the total PDP lead time. As a contribution, the study demonstrates the applicability of Lean Product Development in sectors still scarcely explored in the literature, such as textiles, while also highlighting the relevance of integrating classical quality tools with lean methodologies. It further suggests the need for future research on the digitalization of VSM and GK, aligning product development with the principles of Industry 4.0 and the circular economy.

Most of the techniques for the cell design (CD) problem in cellular manufacturing (CM) consider only the machine-part incidence matrix as the input. They then convert this matrix into a block diagonal form to create a dedicated and independent cell for each part family, without laying out machines. Yet due to the lack of information on the layout, hence the lack of information on the performance of the shop floor, the benefits of CM cannot be validated. Furthermore, operational issues, e.g. scheduling, have an effect on the CD. However, current techniques are not comprehensive enough for a complete CD which should consider the aforementioned issues as a whole. This paper proposes a two-phase method based on total manufacturing lead time (MLT) reduction to overcome these drawbacks. In the first phase, the system is simulated by considering all of the operational issues under the assumption of zero material handling times to minimize total MLT. Besides minimized total MLT, the first phase also yields the waiting times of parts and the volume of the parts-flow between machines, which are used to find similarity measures between machines in the second phase. The second phase then exploits an algorithm which creates and uses these similarity measures to construct a layout by locating machines with higher similarity next to each other to justify the assumption of minimal total MLT and to minimize total material handling time.

During the process of distribution of high-value and time-varying products (HVTVP) by e-commerce retailers, there exists a mismatch between product delivery lead time and customer required time. Within this context, the composition and reduction mode of delivery lead time were studied, and two types of multi-stage lead time reduction models were established. The first type is based on a controllable lead time reduction model and primarily considering the interaction between the different components of lead time reduction, a multi-stage lead time reduction model was bulit with the goal of minimizing total cost. The second type of model considers the impact of product life cycle on cost and lead time reduction. Based on a comparison of the reduction of lead time in different stages and the quantity of products handled, a multi-stage lead time reduction model is created with the goal of maximizing profit. The application of these models demonstrates that the first type can be used to select components of lead time reduction, and the second type can be used to select components of lead time reduction. Finally, the numerical analysis shows the practicality and consistency of the models.

Reduction in lead time is very essential in every industry to increase the productivity, satisfy the volatile demands of a customer and sustain the market reputation among the global industries. The competition among the global industries has forced almost all industries to adopt the lean manufacturing system over the traditional manufacturing system. The present study focuses on the identification of barriers which resist the reduction of lead time in electronics industries in Himachal Pradesh. Nine critical barriers were found on the basis of data collected from the industry experts through the questionnaire survey and consultation from the different regions of Himachal Pradesh. Reduction in lead time is very important for any industry. There are always some barriers which resist the lead time reduction. Industries should know which barrier is most influencing barrier, selection of most influencing barrier can help the industries to overcome from barrier. This study investigates and ranks the barriers in lead time reduction based on the judgement of industry experts from electronics industry. Analytical hierarchy process (AHP) is used to prioritise the barriers.

BackgroundRising incidence and prevalence of end-stage renal disease is a worldwide concern for sustainability of healthcare systems and societies. Living donor renal transplant [LDRT] provides highest health achievements and cost containment than any alternative form of renal replacement therapy. Nonetheless, about 25% of potential LDRTs are missed for causes directly related with inadequate timing in donor assessment. Our quality improvement (QI) project implement process control tools and strategy aiming at reducing total evaluation time for donor candidates and minimizing dialysis exposure for intended recipients, which are the two main determinants of clinical outcomes and costs.MethodsThe study includes patients who underwent donor nephrectomy between January 1, 2017 and December 31, 2021. Six Sigma DMAIC approach was adopted to assess Base Case performance (Jan2017-Jun2019) and to design and implement our QI project. Study of current state analysis focused on distribution of time intervals within the assessment process, analysis of roles and impacts of involved healthcare providers and identification of targets of improvement. Improved Scenario (Jul2019-Dec2021) was assessed in terms of total lead time reduction, total pre-transplantation dialysis exposure and costs reduction, and increase in pre-emptive transplantations. The study was reported following SQUIRE 2.0 Guidelines for QI projects.ResultsStudy population includes 63 patients, 37 in Base Case and 26 in Improved Scenario. Total lead time reduced from a median of 293 to 166 days and this in turn reduced pre-transplantation dialysis exposure and costs by 45%. Rate of potential pre-emptive donors’ loss changes from 44% to 27%.ConclusionsLean methodology is an effective tool to improve quality and efficiency of healthcare processes, in the interest of patients, healthcare professionals and payers.

Total quality management and new product development

Manufacturing systems design must provide effective solutions to cope with the demand during the whole system life-cycle. The problem consists of selecting the appropriate set of resources which best fits the requirements of the addressed production problem. When the demand is characterized by a family of products undergoing technological and volume modifications, the system design process becomes quite complicated. Starting from present and forecasted information, machine tool builders have to design systems endowed with the flexibility and reconfigurability levels that enable the system to face the production problem variability during its life. In spite of the relevance of this topic, there is a lack of tools to explicitly design system flexibility and reconfigurability considering the uncertainty affecting the problem. By addressing two main types of uncertainty, i.e. demand variability and resource availability, this chapter presents a solution method based on multi-stage stochastic programming, to support the design of new manufacturing system architectures whose level of flexibility is focused on the specific production requirements. The problem variability is modeled through scenario trees and the solution is a capacity plan with an initial system configuration and possible reconfigurations. Testing experiments have been carried out considering an industrial case to study the benefits that this approach can offer to machine tool builders.

Requirements reuse has been recently pointed out as one of the most pressing needs and grand challenges in Requirements Engineering. To cope with this demand, this work presents a systematic requirements reuse approach in the Model-Driven Software Development context. The proposal revolves around REMM, a Requirements Engineering MetaModel, which has been recently extended to provide variability modeling mechanisms, which enable requirements reuse. The REMM-Studio+graphical modeling tool, built to support the new modeling capabilities of REMM, now enables the specification of both (1) catalogs of reusable requirements models (modeling for reuse), and (2) specific product requirements, by reusing previously defined requirements (modeling by reuse).

Strategies for the regulation of animal growth have evolved over the last several decades to serve two primary purposes: (1) to increase the efficiency and total amount of meat and milk production, and (2) to improve the nutrient composition of meat animals. The first objective has been pursued with success for over 50 years, providing us with such historical developments as genetic selection for increased rate of gain and improved feed conversion, the use of a large-mature-size breed of sire, the use of nonprotein nitrogen in ruminant diets, the discovery of the growth-promoting effects of antibiotics, antibacterial, and antiparasitic drugs, and more recently the use of the ionophores or rumen modifiers, anabolic and xenobiotic agents. Genetics will probably always be an important aspect of meat animal growth performance, recognizing the value of a diverse gene pool to provide the combination of traits best suited to specific environmental circumstances or specific production requirements. Genetic manipulation now appears to provide great promise for many of the animal science disciplines involved with improving animal performance.

Specialty natural rubber (SpNR) latex, namely, deproteinized natural rubber (DPNR) latex and epoxidized natural rubber (ENR) latex, has been produced to meet specific product's requirements. However, SpNR is normally used in the form of block rubber to manufacture dry rubber products such as tires and automotive parts. The applications of SpNR latex into latex foam products will be diversified. Findings indicate that foamability of SpNR latex is lower compared to normal latex (LATZ) but shows longer stability time after foamed. Findings also indicate that foam collapse and foam coagulate are two main challenges in the fabrication process of SpNR latex foam. Despite these challenges, SpNR latex foam can be fabricated at different density levels. During the foaming process, additional foaming agent is required to fabricate a SpNR latex foam, which is different from fabricating a normal NR latex foam, especially at low latex foam density. Consequently, a higher level of sodium silicofluoride, used as the gelling agent, is required to set the cell structure of the foam. Findings also indicate that foam density influenced the gelling time and volume shrinkage of the SpNR latex foam. An ideal compounding, foaming, and gelling formulation to fabricate SpNR latex foam via Dunlop batch foaming process has been developed. Morphological study showed that all latex foams are open-cell structure, with lower density foam exhibiting higher porosity and mean pore size. Comparison on hysteresis behavior between DPNR and ENR latex foam indicated that ENR latex foam exhibits higher hysteresis loss ratio compared to DPNR latex foam.

Although the benefits of Radio Frequency Identification Technologies (RFID) are quite well known, they are still scarce applications to agriculture and food supply chains. The aim of this study was to determine the extent to which the adoption of RFID can improve supply chain performance in agri-food supply chains. The methodology was a case study of a fruit cooperative using semi-structured interviews and other sources of evidence in order to examine the supply chain performance before and after the RFID implementation. Benefits from the RFID implementation were classified into two broad categories: strategic and operation ones. Strategic benefits included: reduction of the warehouse costs; reduction of total lead time from production to sales; improvement of customer relationship management; improved recall management. Operational benefits included: Better handling of unforeseen events; reducing lead times in warehousing and inventory; improved quality control.

In apparel supply chains, manufacturers usually request a short lead time for fabric supplies. However, a short supply lead time would create environmental problems such as insufficient time for proper control of chemicals and material processing operations, and lead to a lower production yield of good quality supplies. Motivated by this observed industrial practice in fabric sourcing and apparel production, we build a stylized analytical model to investigate how lead time reduction in fabric sourcing affects performances of the fabric supplier and apparel manufacturer as well as the environment. To be specific, we first derive the optimal ordering quantity for the apparel manufacturer and find that it is a production yield scaled newsvendor fractile quantity. We then explore the expected values of lead time reduction, and derive the respective analytical conditions for the apparel manufacturer, fabric supplier and whole supply chain to be benefited by lead time reduction. From the conditions, we reveal that the prior demand mean (which also implies the relative prior demand uncertainty) plays a critical role in determining whether lead time reduction is beneficial. We illustrate how a win–win situation in the supply chain can be achieved by a properly designed deposit payment scheme. For the environment, we show that when the fabric supplier’s profit is improved under lead time reduction, the environment must be hurt. We further investigate how an environment tax can be imposed on the fabric supplier so as to entice it to invest in green technologies.

Lead time reduction and process enhancement for a low volume product

Lead time reduction is a key concern of many industrial buyers of capital facilities given current economic conditions. Supply chain initiatives in manufacturing settings have led owners to expect that dramatic reductions in lead time are possible in all phases of their business, including the delivery of capital materials. Further, narrowing product delivery windows and increasing pressure to be first-to-market create significant external pressure to reduce lead time. In this paper, a case study is presented in which an owner entered the construction supply chain to procure and position key long-lead materials. The materials were held at a position in the supply chain selected to allow some flexibility for continued customization, but dramatic reduction in the time-to-site. Simulation was used as a tool to consider time-to-site tradeoffs for multiple inventory locations so as to better match the needs of the construction effort.

ABSTRACTThe pressure to reduce inventory investments in supply chains has increased as competition expands and product variety grows. Managers are looking for areas they can improve to reduce inventories without hurting the level of service provided. Two areas that managers focus on are the reduction of the replenishment lead time from suppliers and the variability of this lead time. The normal approximation of lead time demand distribution indicates that both actions reduce inventories for cycle service levels above 50%. The normal approximation also indicates that reducing lead time variability tends to have a greater impact than reducing lead times, especially when lead time variability is large. We build on the work of Eppen and Martin (1988) to show that the conclusions from the normal approximation are flawed, especially in the range of service levels where most companies operate. We show the existence of a service‐level threshold greater than 50% below which reorder points increase with a decrease in lead time variability. Thus, for a firm operating just below this threshold, reducing lead times decreases reorder points, whereas reducing lead time variability increases reorder points. For firms operating at these service levels, decreasing lead time is the right lever if they want to cut inventories, not reducing lead time variability.