Application of product family design for engineered systems in changing market space

The focus of this paper is on the design of an engineered system for a changing market space. Due to the dynamic nature of the customer requirements, the specification of product offerings in a particular market may change. Manufacturers need to strategically design their product portfolio in such a way that their profitability is maximized, while deploying the right number of platforms necessary for deriving product variants. Depending on the system architecture, subsystems can be classified into one of the two types: scalar subsystems and modular subsystems. Each subsystem is defined by various parameters, performance criteria, and physical compatibility constraints. The market demand is modeled as a function of selling price and performance criteria. The objective function is formulated as maximization of total profitability for the current and future markets while meeting the required performance criteria. The profitability of an individual unit is the difference between the selling price and cost of that particular unit. The selling price has been expressed as a linear function of system characteristic and performance parameters. The cost of an individual system is the sum of the cost of all the subsystems involved. The cost of an individual subsystem is a function of parameters of that particular subsystem. Further, different types of technology are considered available at different time periods that impacts the switchover cost. The total profitability is further reduced by the platform development cost of the variants. The complete engineered system level problem is formulated as a non-linear programming optimization problem and solved using the non-linear generalized reduced gradient algorithm. The application of the proposed methodology is demonstrated using a case example of an automotive truck family --Abstract, page iv

An integrated Bayesian-Markovian framework for ascertaining cost of executing quality improvement programs in manufacturing industry

Purpose Typically, the budgetary requirements for executing a supplier’s process quality improvement program are often done in unstructured ways in that quality improvement managers purely use their previous experiences and pertinent historical information. In this backdrop, the purpose of this paper is to ascertain the expected cost of carrying out suppliers’ process quality improvement programs that are driven by original equipment manufacturers (OEMs). Design/methodology/approach Using inputs from experts who had prior experience executing suppliers’ quality improvement programs and employing the Bayesian theory, transition probabilities to various quality levels from an initial quality level are ascertained. Thereafter, the Markov chain concept enables the authors to determine steady-state probabilities. These steady-state probabilities in conjunction with quality level cost coefficients yield the expected cost of quality improvement programs. Findings The novel method devised in this research is a key contribution of the work. Furthermore, various implications related to experts’ inputs, dynamics related to Markov chain, etc., are discussed. The method is illustrated using a real life of automotive industry in India. Originality/value The research contributes to the extant literature in that a new method of determining the expected cost of quality improvement is proposed. Furthermore, the method would be of value to OEMs and suppliers wherein the quality levels at a given time are the function of quality levels in preceding period(s)

A supplier performance evaluation framework using single and bi-objective DEA efficiency modelling approach: individual and cross-efficiency perspective

In view of complexities associated with supplier performance evaluation based on traditional business criterions (such as costs, quality levels, and delivery timelines) and emerging criterions (such as those related to environmental sustainability), we in this research evolve two different supplier efficiency measurement models that unify such criterions possessing characteristics of both desirable and undesirable outputs. The first model is a single-objective DEA efficiency assessment model wherein both types of outputs are integrated into a single composite efficiency measure. Using data from suppliers of Hyundai Steel Company, we determine composite efficiencies of each of these suppliers thus ranking them in terms of an overall efficiency score that would be useful as far as the first-cut supplier discrimination is concerned. However, due to the relative inability of evolved single-objective efficiency model to perform trade-offs amongst desirable and undesirable outputs and, owing to unidimensionality aspects, we evolve a goal programming based bi-objective efficiency model wherein trade-offs can be performed between both conventional and emerging dimensions criterions leading to different supplier evaluations for varied scenarios. We also integrate our evolved models with the cross-efficiency view of efficiency determination in order to enable the decision-makers to achieve peer-to-peer evaluation and maximum discrimination amongst suppliers

The impact of Industry 4.0 implementation on supply chains

Purpose The study aims to analyse the impact of Industry 4.0 implementation on supply chains and develop an implementation framework by considering potential drivers and barriers for the Industry 4.0 paradigm. Design/methodology/approach A critical literature review is performed to explore the key drivers and barriers for Industry 4.0 implementation under four business dimensions: strategic, organisational, technological and legal and ethical. A system dynamics model is later developed to understand the impact of Industry 4.0 implementation on supply chain parameters, by including both the identified driving forces and barriers for this technological transformation. The results of the simulation model are utilised to develop a conceptual model for a successful implementation and acceleration of Industry 4.0 in supply chains. Findings Industry 4.0 is predicted to bring new challenges and opportunities for future supply chains. The study discussed several implementation challenges and proposed a framework for an effective adaption and transition of the Industry 4.0 concept into supply chains. Research limitations/implications The results of the simulation model are utilised to develop a conceptual model for a successful implementation and acceleration of Industry 4.0 in supply chains. Practical implications The study is expected to benefit supply chain managers in understanding the challenges for implementing Industry 4.0 in their network. Originality/value Simulation analysis provides examination of Industry 4.0 adoption in terms of its impact on supply chain performance and allows incorporation of both the drivers and barriers of this technological transformation into the analysis. Besides providing an empirical basis for this relationship, a new conceptual framework is proposed for Industry 4.0 implementation in supply chains

IN VITRO ABSORPTION STUDY OF CARBAMAZEPINE SOLID DISPERSION USING EVERTED GUT SAC METHOD

The oral Bioavailability of BCS (Bio Pharmaceutical Classification System) class II drug with poor solubility and reasonable permeability is limited by drug dissolution. In order to improve the aqueous solubility of the drug and dissolution of thedrug, the solid dispersion was prepared and evaluated for its absorption in intestine using modified everted gut sac method. The solid dispersion of carbamezepine (CBZ) was prepared using polaxomer and guargum by kneading method. The CBZ and CBZSD (Solid Disposisi) shows 2.329% and 3.948% drug absorption, respectively. The data show that solid dispersion increase the absorption of the CBZ in CBZ-SD is more than 70% in comparison to pure CBZ. The increase in CBZ solubility of the SD could be attributed to several factors such as improved wettability, local solubilization, drug particle size reduction and crystalline or, interstitial solid solution reduction. Key words: Everted gut sac method, solid dispersion, absorption, solubilit

Clinical Profile and Outcomes of COVID-19 in Renal Transplant Recipients

There is minimal information on coronavirus disease 2019 (COVID-19) in developing countries regarding renal transplant recipients (RTRs). This paper aimed to study the clinical profile, immunosuppressive regimen, treatment, and outcomes in an RTR with COVID-19. This retrospective study was conducted in the nephrology department of Sri Aurobindo Medical College & Postgraduate Institute, Indore (MP), India, from April 1, 2020 to December 15, 2020. We studied 15 patients, of which 13 were treated at our hospital and two were treated in OPD. The median age of transplant recipients was 45 (Interquartile range [IQR]: 26–62) years, the majority being males, and recipients presented at a median of 4 (IQR: 0.3–11) years after transplant. The most common comorbidities included hypertension in 14 (94%) and diabetes 3 (20%) patients. The presenting symptoms at presentation were cough (80%), headache (52%), fever (46%), and breathlessness (26%). Clinical severity as per computerized tomography (CT) severity score ranged from mild (20%), moderate (53%), and severe (27%). Strategies to modify immunosuppressants included discontinuation of antimetabolites without changes in calcineurin inhibitors and steroids (100%). Antiviral therapy (Favipiravir and Remdesivir) was associated with better outcomes and reduced hospital stay. Risk factors for mortality included ABO-incompatibility, severity of disease, high Coronavirus Disease 2019 (COVID-19) Reporting and Data System (CO-RADS) score, allograft dysfunction before COVID-19 infection, acute kidney injury, elevated inflammatory markers, and intensive care unit/ventilator requirement. Overall patient mortality was 13.2%. Risk factor for mortality in COVID-19 positive with RTR appears to be ABO-incompatible transplant, having a previous history of rejection, and patient requiring ventilatory support

An Emerging Trend in Tablet Technology:- Floating Tablets of Ranitidine HCl

The rationale of this research was to prepare a gastroretentive drug delivery system of Ranitidine HCL. Floating Drug delivery system used to target drug release in the stomach or to the upper part of the intestine. The oral delivery of Ranitidine is tested by preparing a non-disintegrating floating dosage form, which increase its absorption in the stomach by increasing the drug’s gastric residence time. The polymer PVC and Sodium bicarbonate was used as the gas–generating agents. Sodium bicarbonate causes the tablets to floats for more then 24hr. The prepared tablets were evaluated on their physicochemical properties and drug release characters. In-vitro release studies indicate that the Ranitidine release form the floating dosage form was uniform followed zero order release. A combination of sodium bicarbonate (70mg) and citric acid (15mg) was found to achieve Optimum in vitro buoyancy. The tablets with methocel K100 were found to float for longer duration of time as compared to formulations containing methocel K15M. The drug release from the tablets was sufficiently sustained.Keywords: Ranitidine; Floating tablets; Methoce

MICMAC Analysis of Industry 4.0 in Indian Automobile Industry

Industrial evolution has taken over as next generation technological breakthrough which is capable of achieving digitalization to ensure enhanced quality, safety and economics. This paper aims to highlight those factors that affect the functioning of the automobile industry. The objective is to find the effect of various factors contributed by Industry 4.0 in the Indian automobile sector through brainstorming with manufacturing experts and literature survey. Ten factors were found relevant. Generated responses were used to measure their influence with each other. Structural Equation Modeling (SEM) analysis was applied for this. Then MICMAC (Matriced'impactscroisés multiplication appliquée á un classment), a cross-impact matrix multiplication is applied to show the dependency of the variables thereby examining the strength of the relationship between Industry 4.0 factors based on their driving and dependence power.The outcome model categorizes the factors in such a way that their impact can be observed by the practitioner and make changes accordingly. Effective mitigation of challenges associated with these factors is envisaged to make it much simpler for the company to enhance their performance and competitive ability. The model reiterates the fact that advancement in technology drives the 4th revolution and other factors such as supply chain management, organizational structure, employment disruption, etc. affect each other at various stages of development

Mitigating demand risk of durable goods in online retailing

Purpose An uncertain product demand in online retailing leads to loss of opportunity cost and customer dissatisfaction due to instances of product unavailability. On the other hand, when e-retailers store excessive inventory of durable goods to fulfill uncertain demand, it results in significant inventory holding and obsolescence cost. In view of such overstocking/understocking situations, this study attempts to mitigate online demand risk by exploring novel e-retailing approaches considering the trade-offs between opportunity cost/customer dissatisfaction and inventory holding/obsolescence cost. Design/methodology/approach Four e-retailing approaches are introduced to mitigate uncertain demand and minimize the economic losses to e-retailer. Using three months of purchased history data of online consumers for durable goods, four proposed approaches are tested by developing product attribute based algorithm to calculate the economic loss to the e-retailer. Findings Mixed e-retailing method of selling unavailable products from collaborative e-retail partner and alternative product's suggestion from own e-retailing method is found to be best for mitigating uncertain demand as well as limiting customer dissatisfaction. Research limitations/implications Limited numbers of risk factor have been considered in this study. In the future, others risk factors like fraudulent order of high demand products, long delivery time window risk, damage and return risk of popular products can be incorporated and handled to reduce the economic loss. Practical implications The analysis can minimize the economic losses to an e-retailer and also can maximize the profit of collaborative e-retailing partner. Originality/value The study proposes a retailer to retailer collaboration approach without sharing the forecasted products' demand information