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Time to market is the essential aim of any new product introduction process. Performance measures are simple quantities that indicate the state of manufacturing organisations and are used as the basis of decision‐making at this crucial early stage of the process. Fuzzy set theory is a method for using qualitative data and subjective opinion. Fuzzy sets have been used extensively in manufacturing for applications including control, decision‐making, and estimation. Type‐2 fuzzy sets are a novel extension of type‐1 fuzzy sets. Aims to examine this subject.

This research explores the increased use of type‐2 fuzzy sets in manufacturing. In particular, type‐2 fuzzy sets are used to model “the words that mean different things to different people”.

A model that can leverage design process knowledge and predict time to market from performance measures is a potentially valuable tool for decision making and continuous improvement. A number of data sources, such as process maps, from previous research into time to market in a high technology products company, are used to structure and build a type‐2 fuzzy logic model for the prediction of time to market.

This paper presents a demonstration of how the type‐2 fuzzy logic model works and provides directions for further research into the design process for time to market.

The purpose of this paper is to report a case study in which artificial neural network (ANN) has been used for performing fuzzy logic based leanness assessment.

Leanness is the measure of lean manufacturing practice. Fuzzy logic has been used for the calculation of leanness. To improve the effectiveness of computation, ANN tool has been used in this study. The network has been modeled, trained and simulated using the MATLAB software.

The disadvantages associated with the scoring method has been overcome by the deployment of fuzzy logic. The problem associated with manual computation has been overcome by the application of ANN. The simulated model has been validated by measuring the leanness level of the case organization.

The case study has been carried out in a single electronic switches manufacturing organization. In the fuzzy logic approach, triangular fuzzy numbers are being used in the present study.

The paper reports a case study conducted in an Indian transformers manufacturing organisation. Hence, the results derived from the study are validated in a real time manufacturing environment.

The idea of applying ANN for fuzzy logic based leanness assessment is the original contribution of the authors.

The purpose of this paper is to provide a management tool to maximise the effective time-to-market of a portfolio given the competitive monitoring activities.

From the constant monitoring of competition and market needs, it is proposed to define a time-to-need, time when the market may consume the product under development and competitor will not provide a solution before. This time-to-need is proposed to be defined by an expert committee in a periodical meeting of the portfolio. Once it is identified the time-to-need and the time-to-market (project management), it is possible to manage resources in order to maximise the portfolio outputs.

The application of the mentioned approach in an automotive industry showed improvements on number of launched new products per year (double) and on number of patented product launched (four times more).

This approach applies on projects of medium to long term (more than two years) because the resource management can consume set up time. The presented results in this work were based in a single case, which can limit the expected results of the application of this methodology.

This approach enables a constant alignment among experts and a better deployment of resources.

This work provides a practical tool to promote better resource allocation in a portfolio. It can also be an enabler of innovation projects once it finds resources potential to fund the more front end work.

Speed to the market is becoming a key competitive priority in developing countries’ environments even though lack of technology, poor skilled labour and under-developed infrastructure remain daunting challenges. The purpose of this paper is to examine the causes and relative importance of delay factors in the introduction of food products to the market in the era of time-based competition.

The study employed a case study approach in understanding the phenomenon in its natural settings and making sense of it through process and participants observations. Again, a two-stage approach (first, interviews and second, questionnaire) was used in collecting data from the respondents who work in a project team for a large food processing firm. The data was analysed using the relative importance index technique.

The results show that the most important causes of delays in new products introduction, especially in the food processing industry, are: high number of projects running concurrently; lack of project management process; lack of consistent project management structure; high workload on project team and delays caused by external laboratory.

This study sought to identify detailed delay factors in the introduction of new products with respect to the food processing industry and more importantly established the relative importance of these delay factors as a decision support system for managers in the food processing industry.