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The purpose of this paper is to investigate the use of steam in order to replace air in the production of spun-like textured yarns. Further, this paper analyse the effect of production speed on process and textured yarn properties.

An existing air-jet texturing machine was modified to supply either air or steam to the texturing nozzle. Using standard commercial nozzles, both air-jet and steam-jet textured yarns were manufactured by varying production speed.

It can be concluded that steam can be used as an alternative fluid for air in making spun-like textured yarns. Results show that yarn parameters for steam-jet texturing show a similar trend to those of air-jet texturing relative to the production speed. Further, sewing threads made from steam-jet textured yarns showed good sewability up to the speeds of 350 m/min.

Only the effect of production speed on process and yarn parameters is discussed in this paper. Production speed was limited to 350 m/min due to machine constraints.

Steam is more economical than air to manufacture spun-like textured yarn at commercial pressures such as 8 bar. Steam-jet textured yarns could be used for commercial applications such as sewing threads at competitive speeds. Further, steam could be generated using sustainable and renewable fuel sources such as biomass.

This research introduced steam as an alternative fluid for air in manufacturing spun-like textured yarns.

The main objectives of this research work were to investigate the effect of production speed on intermingled yarn properties and melange fabric properties with special reference to melange appearance.

Polyester/nylon intermingled yarns were produced using an SSM DP3-C air-intermingling machine using commercial process parameters and Heberlein P212 nozzle. Melange fabric samples were knitted from polyester/nylon intermingled yarns while maintaining the same parameters to avoid knitting variations. The fabric samples were dyed using a sample dyeing machine while maintaining dye recipe and dyeing parameters constant to avoid dyeing variations.

The production speed has significant effect on intermingled yarn and melange fabric properties. When the production speed is increased, mingle points, mingle stability, linear density, strength and the elongation of the intermingled yarns decreases. When the production speed is increased, fabric weight decreases and the melange effect varies from dot-like appearance to line-like appearance.

Only the effect of production speed on intermingled yarn and melange fabric properties is discussed in this paper. Appearance evaluating systems developed in this research are limited to melange fabrics produced using air-intermingled yarns with two colour components.

Results indicate that the intermingled yarns for the application of melange fabrics should be developed with optimum intermingling speeds, and it should not be changed during the production since production speed has significant effect on yarn and fabric parameters. Therefore, melange appearance and fabric weight may vary between fabric lots with different production speeds even though all the other parameters are kept constant. Further, melange appearance evaluation method developed in this research could be used as a guide in developing melange fabrics.

This research introduced a qualitative and a quantitative method to analyse melange fabric appearance. This melange appearance evaluation method can be used as a guide to achieve specific melange effect in the sample development stage. Further, when a melange sample appearance catalogue is developed for all the variables for a particular fabric type using this evaluation method, customer requested appearance can be achieved in minimum sample trials which save time, capacity, money and customer credibility.

The purpose of this paper is to reduce or eliminate the overall equipment effectiveness (OEE’s) speed loss in a lean manufacturing environment.

This action research study uses the lean manufacturing 5-whys analysis technique to reduce or eliminate the speed loss.

The application of the 5-whys analysis technique in a manufacturing industry (XYZ Corporation) completely eliminated its top speed loss and resulted in a valuable savings of USD 32,811.5 per annum.

The 5-whys analysis technique which has been primarily known to improve the OEE’s quality loss and changeover loss has been proven to be an effective approach to also tackle speed loss; a loss which has been regarded as the most dominating loss among all the types of OEE’s losses and a difficult one to eliminate.

Little or no attempt has been made to date to expand the use of the 5-whys analysis technique beyond its originally intended purpose. The lessons learnt in this study could be applied to other organizations. The outcome of the study has also opened the possibility of widening the horizon of the use of the 5-whys analysis technique beyond its original intended objective and could be applicable to solve other losses of OEE and non-value added activities of lean philosophy in general.

This research integrates maintenance planning and production scheduling from a green perspective to reduce the carbon footprint.

A mixed-integer nonlinear programming (MINLP) model is developed to study the relation between production makespan, energy consumption, maintenance actions and footprint, i.e. service level and sustainability measures. The speed scaling technique is used to control energy consumption, the capping policy is used to control CO2 footprint and preventive maintenance (PM) is used to keep the machine working in healthy conditions.

It was found that ignoring maintenance activities increases the schedule makespan by more than 21.80%, the total maintenance time required to keep the machine healthy by up to 75.33% and the CO2 footprint by 15%.

The proposed optimization model can simultaneously be used for maintenance planning, job scheduling and footprint minimization. Furthermore, it can be extended to consider other maintenance activities and production configurations, e.g. flow shop or job shop scheduling.

Maintenance planning, production scheduling and greenhouse gas (GHG) emissions are intertwined in the industry. The proposed model enhances the performance of the maintenance and production systems. Furthermore, it shows the value of conducting maintenance activities on the machine's availability and CO2 footprint.

This work contributes to the literature by combining maintenance planning, single-machine scheduling and environmental aspects in an integrated MINLP model. In addition, the model considers several practical features, such as machine-aging rate, speed scaling technique to control emissions, minimal repair (MR) and PM.

The problem of diverse cash flows associated with a construction “project” appear in four progressive cycles. These are the initiating construction cycle and closing deconstruction cycle (devaluation cycle). The effectiveness of any project is given by capitalisation cycle. The optimisation of payback (credit return) cycle is critical for any project.

For calculate of activity durations, cash flows and even we may use the spreadsheet table as a tool for expression of calculation formulas. This approach may offer a mechanism for answers regarding the sensitivity of manageable parameters (say changes in costs, construction speeds, duration of activity). The problem of optimal capacity expansion of construction work as a time dependent problem is studied in many different applied contexts. Traditional capacity planning usually begins with a forecast of demand on the basis of organisational or technological needs.

The implementation of a technical project carried out in conditions of high production speeds and low time reserves requires changes in technologies, organisation and preparation of construction. In each specific case, a civil engineer needs to know the economic impacts (the capability of applicable calculations).

It is obvious from the given example, which has the same features as the execution of a series of construction projects in recent years, that the myth of the importance of executing works in large volumes ahead of the deadlines has significant financial consequences.

This paper, from the perspective of based view of dynamic system, aims to take the family enterprise as a sample to articulate how the speed of institutional change affects the entrepreneur’s spirit collocation of family enterprises and investigate the moderating effects of the scale of enterprises as well.

This paper uses survey database from Chinese research of private enterprise group in 2010 with the ninth national large-scale private entrepreneurs, and the legal source of data comes from research center for Chinese family firm of Sun Yat-Sen University. A total of 4,900 questionnaires are issued, 4,614 are recovered and the total recovery rate is 94.16 per cent. In this paper, STATA12.0 is used for data processing and basic regression testing. To overcome the possible existence of the different variance problem, the authors use the feasible generalized least squares to estimate the model.

The speed of institutional change will lead to the reduction of unproductive activities and the increase of productive activities in the area where the speed of institutional change is slow. Meanwhile, the scale of enterprise can reverse the negative relationship between the speed of institutional change and unproductive activities. The speed of institutional change will lead to the reduction of unproductive activities and the increase of productive activities in the area where the speed of institutional change is fast. Meanwhile, the scale of enterprises can reverse the positive relationship between the speed of institutional change and the unproductive activities.

It can be concluded that because of the difference of the regional market, a positive U-type reflects the relationship between the speed of institutional change and the entrepreneur’s allocation of entrepreneurship in family firms, whereas the scale of enterprises plays a key role of nonlinear regulation. This research has a certain theoretical value and practical significance on the understanding of how family firms make strategic decisions in response to institutional change and it can further enrich the research results of entrepreneurship allocation theory and institutional change theory.

This paper aims to develop a decision support system for predicting the knitting production’s efficiency based on the input parameters of an order. This tool supports the operations managers to make reliable decisions of estimated delivery time, which will result in reducing waste arising from late delivery, overtime and increased labor.

The decision tree method with a set of logical IF-THEN rules is used to determine the knitting production’s efficiency. Each path of the decision tree represents a rule of the following form: “IF <Condition> THEN <Efficiency label>.” Starting with identifying and categorizing input specifications, the model is then applied to the observed data to regenerate the results of efficiency into classification instances.

The production’s efficiency is the result of the interaction between input specifications such as yarn’s component, knitting fabric specifications and machine speed. The rule base is generated through a decision tree built to classify the efficiency into five levels, including very low, low, medium, high and very high. Based on this, production managers can determine the delivery time and schedule the manufacturing planning more accurately. In this research, the correct classification instances, which is simply a ratio of the correctly predicted observations to the total ones, reach 80.17%.

This research proposes a new methodology for estimating the efficiency of weft knitting production based on a decision tree method with an application of real data. This model supports the decision-making process of the estimated delivery time.

Given the need to simultaneously implement lean and agile (LeAgile) paradigms in supply chain, managers do not know which of these paradigms practices should be given priority. Not knowing this, not only will they fail to apply these paradigms properly, but they will also waste significant financial resources. The purpose of this paper is to investigate the relationship between the practices of LeAgile paradigms and their effects on the supply chain performance.

Because the military products play a key role in national security enhancement, this research is done in the military product supply chain. Research methodology is an exploratory, mixed and descriptive one. In terms of its purpose, it is an applied research based on identifying and searching for practices and the use of interpretive equations. First, the authors identify the most important and implementable LeAgile practices in the form of importance feasibility analysis matrices. Then, using fuzzy interpretative structural modeling, a model is presented to show the logical relationships and hierarchy between paradigms, practices and their impact on supply chain performance. The research tool in both main stages of the research was the questionnaire completed by industrial and academic experts. The selection of experts was done purposefully.

The results show that of total 100 practices introduced in the previous research for LeAgile supply chain, 21 practices in the lean and agility of the supply chain of military industries are important and implementable. The final model of this study illustrates the hierarchical relationships between 21 practices and its effect on supply chain performance key measures. This model shows that LeAgile paradigms are intertwined and their simultaneous implementation leads to improved supply chain performance. In this model, supplier-related practices play a driving and fundamental role and become a top priority for implementation.

Military products variation in land, air and sea areas and the large number of industries in each sectors, forced us to select the only land area. Although the results of this research can be used in the air and sea areas, one cannot say that Implementation of this study by its presented model will fully lead to the military industries supply chain (SC) lean and agility in air and sea sectors.

To the best of the authors’ knowledge, this is the first research on the SC legality in Iran’s military industry which tries to apply these two paradigms simultaneously in the SC and bridge the gap between theory and practice. Clustering LeAgile practices, based on two measures of importance and feasibility, and defining four strategies for implementing these measures, is a new approach to focus on deploying practices that are currently more feasible. Identifying a significant number of SC LeAgile practices (100 practices) and demonstrating the interactions between important and feasible practices in the military products SC are another innovation in this research.

As overall equipment effectiveness (OEE) is a metric to estimate equipment effectiveness of production systems, the purpose of this paper is to identify strategic management tools and techniques based on OEE assessment of the ice cream production line.

This paper presents the collection and the analysis of data for ice cream production under real working conditions. The data cover a period of eight months. A framework process to improve the OEE of an automated production system was proposed. Six major stoppage losses, i.e. equipment failure, setup and adjustment, idling and minor stoppage, reduced speed, defects in the process, and reduced yield, were examined with the help of Pareto analysis. In addition, the actual availability (A), performance efficiency (PΕ) and quality rate (QR) measures, together with the complete OEE for each working day, week and month of the production line were shown.

The main goal of the study is to identify major stoppage losses, in order to examine and improve the overall equipment efficiency (OEE) of the ice cream production line through the application of an adequate management, i.e. TPM approach. Based on the obtained results, maintenance management strategy and production planning have been suggested to improve their maintenance procedures and the productivity as well.

The proposed method can be applied to each automated production system. The main benefits of this method are the improvement of productivity, quality enhancement of products, the reduction of sudden breakdowns and the cost of maintenance. Moreover, the analysis provides a useful perspective and helps managers/engineers make better decisions on the operations management of the line, and suggestions for improvement were proposed and will be implemented accordingly.

An aggregate production function has been used in macroeconomic analysis for a long time, even though it seems that it is conceptually confusing and problematic. The purpose of this paper is to argue that the measurement problem related to the heterogenous capital input that exists in macroeconomics is also relevant to microeconomic market situations.

The author constructed a microeconomic market model to address both the problems of the measurement of the physical capital and of substitutability between labor and capital in the short run using two types of technologies: labor neutral and labor reducing. The author proposed that labor and physical capital inputs are complementary in the short run and can become substitutes only in the long run when the technology advances.

The author found that even if the technology improves at a fast rate over time, there are then diminishing returns of profits to technology and an upper limit to profits. Moreover, the author showed that under the labor-reducing technology, labor class earns more initially as technology improves, but their incomes start declining after some threshold level of passage of time.

The author cautioned the applied researcher that the estimated labor and capital coefficients of generalized Cobb–Douglas and constant elasticity of substitution of types of production functions could not be interpreted as partial elasticities of labor and capital if in reality the data come from fixed-proportions types of processes.