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In the DOS world, Windows 3.0 is an operating environment that utilizes a Graphical User Interface, or “GUI.” A GUI is an alternative to typing as a means of interacting with the computer and its operating system that is intended to be superior, in some ways, to the operating system itself. It is not a replacement for the operating system (e.g., DOS 3.31 or DOS 5.0). The principal features and strengths of Windows 3.0 are examined, as is a suite of programs—Word for Windows, Excel for Windows, and PowerPoint for Windows—which are collectively packaged as Microsoft Office for Windows. While not “perfect,” there is a significant advantage to the uniformity of the Windows environment.

In this study, a tool has been designed and developed for learning about the concept of lag order within a dynamic model, which can be used in any teaching classes on statistics and financial data computation. To show a solution for a complex and multi-step process of finding the optimal lag order for multiple variables data series based on an information criterion a module using Visual Basic for Applications (VBA) for Microsoft Excel (MS Excel) is being developed. This module can be used for estimating a multivariate dynamic model as well as determining the optimal lag order of such a model.

This study aims to demonstrate the application of process mapping and simulation, using popular software tools, by examining a paper sheet cutting operation.

An integrated approach is utilized to model a sheeting operation at Advance Agro, PCL, Thailand, a pulp and paper manufacturer. The sheeting operation is one of the most critical operations. The redesigned sheeting operation resulted in setup time reduction. This was carried out by studying the process map, data analysis, and simulation of the redesigned operation (using Visio, Excel and Arena software) before a real implementation at the manufacturing plant. The simulation of redesigned sheeting process showed increase in productivity and annual cost savings.

Case experiences indicate that combining process mapping and data analysis with simulation is beneficial. The computer‐based integrated approach successfully reduces the risk of ineffectiveness of the redesigned critical manufacturing operation. In the new improved operation, higher machine utilization results in both reduced lead time and availability of more free time for operators to carry out quality inspections leading to better quality products.

The computer simulation of redesigned sheeting operation showed existing machines can handle more orders and result in higher production and lower unit cost than the existing sheeting operation. The productivity increase for the manufacturer with the new sheeting strategy was expected to be worth US $450,000 annually.

The study makes a business case that process improvement can be effectively accomplished with an integrated approach of using widely available inexpensive and user‐friendly computer‐based tools. It also showcases a good practice in manufacturing system redesign.

In the ‘old days’, throughout the 1970s and early 1980s, the adage in the IT industry used to be ‘Nobody ever gets fired for buying IBM’. IBM would sell complete solutions, hardware and software (operating systems and applications) to meet all needs. These days it is more likely to be ‘Nobody ever gets fired for buying Microsoft’. Microsoft do not sell complete solutions. The only hardware they currently sell are ergonomic keyboards, mice and game accessories. Their dominance comes solely from their software.

A major factor to the success of flexible manufacturing systems (FMSs) is their ability to transport work pieces between different workstations. FMS have now become more advanced and material‐handling systems have become progressively more sophisticated, it is not exceptional to have automated steering of tools to workstations as well. Such system design will improve the tool‐handling capability and the system productivity while holding tool cost to a minimum. Tool cost could represent as much as 25 percent of the operating cost. The purpose of this paper is to propose a new colored Petri net (CPN)‐based approach to the design and development of a tool sharing control system that is intended to help use of the proper and minimal number of tools for a manufacturing system.

A new black token timed PN model is first developed, to reduce the complexity of the graphical representation a new CPN model is developed. The new CPN model also allows to find the optimal sequence. The optimal sequence has no effect on the work in process (WIP) but it influences the number of tools used in the system. The main input to the PN model for a manufacturing system is the process plan. Next, all the invariants and total number of possible elementary circuits are determined using the Integrated Net Analyzer (INA) software. Output from the INA software is exported to the Excel spreadsheet. The Excel spreadsheet can be designed to calculate the total number of tokens, processing time, cycle time, etc. of each elementary circuit. Subsequently, the constraints used in Lingo will be created according to critical circuit rules. Finally, linear programming (LP) technique is used to optimize the WIP and tool inventory. Lingo software is used for the LP, the constraints from the Excel sheet will be the input data to the Lingo program, and based on those constraints the Lingo will provide the optimal values for the desired parameters. The output from Lingo will be used to recalculate the cycle time of each elementary circuit in the Excel sheet. The system is then analyzed before and after the implementation of the CPN model.

A new CPN model based on tool‐sharing philosophy for an FMS with N part types and M stations is proposed.

The paper presents a new CPN‐based approach to the design and development of a tool sharing control system, that is, intended to help use of the proper and minimal number of tools for a manufacturing system. The new CPN model also allows to find the optimal sequence. The idea is new and pure and has not been presented before using the methodology adopted in this paper.

The purpose of this paper is to develop a dynamic, stochastic, mechanistic simulation model of a dairy business to evaluate the cost and benefit streams coinciding with technology investments. The model was constructed to embody the biological and economical complexities of a dairy farm system within a partial budgeting framework. A primary objective was to establish a flexible, user‐friendly, farm‐specific, decision‐making tool for dairy producers or their advisers and technology manufacturers.

The basic deterministic model was created in Microsoft Excel (Microsoft, Seattle, Washington). The @Risk add‐in (Palisade Corporation, Ithaca, New York) for Excel was employed to account for the stochastic nature of key variables within a Monte Carlo simulation. Net present value was the primary metric used to assess the economic profitability of investments. The model was composed of a series of modules, which synergistically provide the necessary inputs for profitability analysis. Estimates of biological relationships within the model were obtained from the literature in an attempt to represent an average or typical US dairy. Technology benefits were appraised from the resulting impact on disease incidence, disease impact, and reproductive performance. In this paper, the model structure and methodology were described in detail.

Examples of the utility of examining the influence of stochastic input and output prices on the costs of culling, days open, and disease were examined. Each of these parameters was highly sensitive to stochastic prices and deterministic inputs.

Decision support tools, such as this one, that are designed to investigate dairy business decisions may benefit dairy producers.

Many modern businesses have accommodation needs which vary sharply over time. Corporate real estate (CRE) managers plan for these variations using “common sense” estimates based on average occupation levels, and these estimates are almost always wrong. This study aims to present a method where these businesses can optimise decisions on their mix of short‐ and long‐term space based on previous occupation patterns.

The optimum accommodation mix is derived from Monte Carlo simulation, where previous work patterns are resampled to estimate future needs. The method is extended to look at the effect of rental costs, and looks at how rental decisions are affected by attitudes to risk. Extensions of the method include pricing of real estate derivatives and assessing the probability of making money from renting premises. The method is easily within the grasp of most spreadsheet users, and can be automated using a number of simple, downloadable tools. This method is suitable for organisations with fluctuating workforces, and will be of special interest to project‐based organisations.

Use of “average” occupancy levels to predict the accommodation mix, while intuitive, produces worse results than simulation. While the method is transferable, the analysis must be performed using the company's specific distribution. The mix depends not only on the ratio of short‐ to long‐term rents, but also on the renter's perception of risk.

The method produces provides more accuracy for accommodation planning in all “real world” cases. The technique also provides an opportunity for the CRE manager to engage with the board about the importance of business planning.

The study describes a simulation method widely used outside the real estate industry, and provides simple side‐bars that will help readers to create their own models using Microsoft Excel.

Micro, small, and medium enterprises (MSMEs) can play a significant role in achieving sustainable development goals (SDGs) as they have the ability to reduce unemployment. Digitalization helps MSMEs in a number of ways, including lowering transaction costs, quickening access to information, and bettering communication with extended supply chain members. This chapter aims to understand the level of digitalization in MSMEs in an emerging economy such as Bangladesh. MSMEs in Bangladesh account for 25% of the gross domestic product and employ 87% of civilians. This chapter builds on qualitative data from 60 MSMEs from various manufacturing and service sectors such as textile, retail, food delivery, IT companies, etc. The interviews were semi-structured and followed an interview protocol. The length of interviews varied between 40 and 50 minutes. Content analysis was used to analyze the data. Findings suggest that counterintuitively the level of digitization in MSMEs is not low in Bangladesh. Many micro and small enterprises use MS Excel to help them manage customer and product data. Medium Enterprises use Enterprise Resource Planning (ERP) software for planning enterprise-wide resources. Some medium enterprises also use powerful data analytics software such as Oracle, Power BI, Google Analytics, Python, and SPSS. Results also reveal barriers to digitization in MSMEs, which include a lack of employee awareness, training, and motivation of top management. This chapter maps the digitalization levels in MSMEs in Bangladesh and provides implications for SGDs. The chapter also presents policy recommendations for improving the digitalization level in emerging economies.

Biopigments, natural colors from microbiological origin are of great interest because of their potential advantages over synthetic colorants. Therefore, this paper aims to evaluate the best possible fermentative conditions for the maximum production of biopigment using solid state fermentation and submerged fermentation by Monascus purpureus MTCC 369.

The biopigment was produced using solid state fermentation and submerged with optimized substrate to achieve higher yield. The statistical analysis was carried out using a Microsoft Excel ® (Microsoft Corporation).

On comparative analysis, it was observed that solid state fermentation resulted significant accumulation of biopigment (9.0 CVU/g) on the 9th day in comparison to submerged fermentation (5.1 CVU/g) on the 15th day.

Results revealed that sweet potato peel powder and pea pods provides necessary nutrients required for mycelial growth, and biopigment production, therefore, can be used as potent substrate for biopigment production by Monascus purpureus MTCC 369. Extracted color can be used in confectionery, beverages and pharmaceutical industries.

This work focuses on utilisation of waste for production of pigment as alternative source to synthetic colorant, and few studies have been carried out using wastes, but no work has been carried out on sweet potato peel to the best of the authors’ knowledge.

Supplier selection is a complex and strategic activity needed in every organization, involving many stakeholders and different attributes as price, delivery performance, and product quality. Globalization, in the last decades, increased the competitiveness between vendors, enhancing the use of decision models to support the best choice based on optimizations and bidding variations due to specific needs. This chapter presents three models of multi-dimensional auctions to improve an international humanitarian NGO process procurement efficiency by reducing procurement costs and the decision-making process time. These models have the advantage to be easily implementable in typically complex environments where there is a large number of categories, suppliers, and other features.

The first proposed model uses combinatorial auctions and is suited for procurement, where suppliers can benefit from cost complementarity. The second one uses volume discount auctions and is suited for volumetric purchases, where discounts for large quantities are common. The third one is a multi-attribute model, which computes the best possible solution considering several criteria and can be used in case of complex purchases that involve various categories and trade-offs and are subject to spot prices.

Several design considerations for this type of auctions are reviewed, as well as the mathematical formulation to determine the best alternative (i.e., winner) that can be solved using simple tools like Microsoft Excel. The models are optimized by a mixed-integer programming, and the multi-attribute one is developed using multi-criteria decision analysis (MCDA). All three models developed in this research showed superior results compared to the baseline, being between 9% and 20% more efficient than a regular supplier selection (singly choosing the lowest price) and improving the bidding compliance.