• Posted on November 16, 2022
• Unique Submission Team

U25188 M452 Operations Management Assignment Sample

PROBLEM 1

A)

For any company, the value of innovation is mostly because to remain in the market company must have to be productive and innovative.

All the manufacturing companies are using different types of technology to become more innovative (MacKenzie et al., 2019). http://U25188 M452 Operations Management Assignment SampleIf the company will be innovative then only it can produce products according to the demand of the customers. To gain a good market share any company must produce goods according to the need and demand of the customers.

For manufacturing companies innovation means the implementation of different types of technology to make the products better and according to the expectation of customers.

All those companies, which have implemented advanced technology to make their products more innovative and according to the market come in the category of the most innovative companies (Yelundur et al., 2017).http://U25188 M452 Operations Management Assignment Sample In manufacturing companies, innovation means advancement in design, supply chain, research and development, and logistics management process.

By implementation of the engineering in the manufacturing process, large-scale production is possible. Implementation of the engineering in the manufacturing department also helps in enhancing the quality of the product.

Many innovations have been done in the manufacturing sector but the most important innovations are those who has made the company to save the time and also helps in satisfying the customers

1. Virtual manufacturing- All the companies are implementing smart manufacturing processes in their manufacturing segment. These are performed virtually. These smart methods are timesaving as well as very precise.

 

2. Micro manufacturing and error detection by machines- micro manufacturing implies the manufacturing of very tiny parts of the different machines. Manufacturing of these micro parts requires very high precision and there is the possibility of error so error detection is also done by using machines.
3. Industrial robotics- this includes the deployment of robots in the manufacturing segment to make the manufacturing process fast and accurate. Implementation of robotics helps in making high precision parts of the different materials.
4. Use of the sensors in the workplace- if different types of sensors will be used in the workplace then it will be very easy to detect different types of Eros in the manufactured products (Foster et al., 2018).http://U25188 M452 Operations Management Assignment Sample Sensors are also used to sense the competency of the different products manufactured in the plants.
5. Automated warehouse and smart recycling of the waste- if these are implemented in the manufacturing process then the manufacturing process will become very fast and if the warehouse will be automated then loading and unloading of the manufactured products will become very easy.
6. 3D printing- this is a fully new concept of manufacturing products many products can be made by using this technology. This technology is very time-saving and very accurate. Many parts of different types of machinery can be manufactured by this method.
7. Ensuring safety at the workplace- during the manufacturing process safety of the workers working there is necessary so the company should implement different types of safety devices at the workplace to ensure the safety of the workers.

All the above-discussed manufacturing methods should be implemented in the company to enhance the value of the products (Aliyev et al., 2018).http://U25188 M452 Operations Management Assignment Sample All the assembling organizations are utilizing various sorts of innovation to turn out to be more creative.

If the organization will be inventive, at that point no one but it can deliver items as per the interest of the clients. To acquire a decent piece of the pie any organization needs to deliver the merchandise as indicated by the need and request of the clients.

For the assembling organization development implies the execution of various sorts of innovation to improve the items and as per the assumption for clients. Each one of those organizations, which have actualized cutting-edge innovation to make their items more imaginative, and as per the market comes in the class of the most creative organizations.

B)

1) Lot sizing is the method to unifying the calculated pure requirements by any manufacturing unit by considering the work efficiency and the cost reduction. It is classified into two parts first is calculated in terms of the period and the second is calculated in terms of the quality.

The lot sizing method, which is calculated, based on the period is dynamic because as the period of the manufacturing changes it also changes and so it comes under dynamic lot sizing. In assembling organizations, advancement implies headway InDesign, store network, innovative work, and calculated administration measures.

Dynamic part estimating strategy used the time frame requested count for the stock hypothesis so on the off chance that the interest of the item changes with the time, at that point chiefs attempt to utilize the unique parcel measuring technique to control the stream. Part estimating procedure which is resolved depends on the period is dynamic because as the hour of the collecting changes it furthermore changes hence it goes under the incredible bundle assessing.

The hoarding affiliations movement deduces progress In Design, store association, inventive work, and decided association measure (Rotella et al., 2020).http://U25188 M452 Operations Management Assignment Sample Package estimating is the procedure for unifying the decided unadulterated necessities by any amassing unit by contemplating the work capability and the cost decline.

By execution of the designing in the assembling cycle, enormous scope creation is conceivable. Execution of the designing in the assembling division additionally helps in upgrading the nature of the item. Lot sizing which is dynamic in nature changes with the period so period depended on lot sizing comes under the category of dynamic lot sizing.

2)  When the demand for a particular product varies with time then managers use the dynamic lot sizing method (Shinoda et al., 2019). http://U25188 M452 Operations Management Assignment Sample

The dynamic lot-sizing method utilized the period demanded calculation for the inventory theory so if the demand of the product changes with time then managers try to use the dynamic lot sizing method to control the flow.

Part measuring technique, which is determined, based on the period is dynamic because as the time of the assembling transforms it additionally changes thus it goes under the powerful parcel estimating. In the amassing associations, progression infers progress In Design, store organization, creative work, and determined organization measure.

Lot sizing is the technique to unifying the determined unadulterated necessities by any assembling unit by thinking about the work proficiency and the expense decrease. It is characterized in two sections first is determined in quite a while of the time frame and the second is determined regarding the quality.

Part estimating strategy, which is determined based on the period, is dynamic because as the time of the assembling transforms it likewise changes thus it goes under the powerful parcel measuring (Durante et al., 2020).http://U25188 M452 Operations Management Assignment Sample In the amassing associations, progression infers progress In Design, store organization, creative work, and determined organization measure.

The dynamic lot-sizing method is utilized the period demanded calculation for the inventory theory so if the demand of the product changes with time then managers try to use the dynamic lot sizing method to control the price.

Problem 2 

Production Planning Problem

1. As per the requirement of the production-planning problem, the purpose of the coursework is to draw an integer-programming model for the production planning program, by scheduling the monthly production levels and all the complementary elements of the manufacturing process (Darmawan et al., 2018). http://U25188 M452 Operations Management Assignment Sample

As mentioned in the problem-

• The total demand for product A in all four prospects is 1650, 670, 1070, and 650.
• The total demand for product B in all four prospects is 10668, 9463, 10604, and 6600.
• The total demand for product C in all four prospects is 2700, 1500, 2000, and 1400.

Here, for the formulation of the linear program, some assumptions are needed to be made to simplify the planning procedure:

1. Assumption 1:

Let us assume there is zero quantity of inventory at the beginning of the first month for product A (Darvishiet al., 2020).http://U25188 M452 Operations Management Assignment Sample Here, let the demand of the product A section one (d1) be 1650 units, and let the production level be 2000 units.

Hence, the initial inventory by the end of the first month will be 0 + 2000 – 1650 = 350 units.

2. Assumption 2:

Let us assume, the produced units of products are immediately available for delivery in the first month for product A.

As the demand (d1) is 1650 units, hence the company must manufacture more than 1650 units during the period of the first month. This will allow the immediate delivery facility and zero shortages.

3. Assumption 3:

Let us assume there is no shortage of inventories in stock by the end of the first month for Product A. Here, demand for the product (d1) is 1650 units, and suppose the c1 = 100 and h1 = 20. Thus, from the computation of the given elements, we can determine the total cost incurred during the first month, which is:

100 × 2000 + 20 × 350 = £ 27000

This is how we can compute the linear program for all the products namely products A, B, and C, with their respective departments of Assemble, Chemical Process, Forge, and Welding.

Decision Variables

The aim is to formulate a monthly linear program level, thus, we will receive twelve distinct variables for each product from each department, which will impact the decision-making of the production programs.

Here,

xj = the monthly production level is j, j = 1, 2, 3…, 12.

Objective Function

Taking into consideration the inventory and demand level of the first month will impact the production model of the organization. According to the assumptions, the production cost of the two variable c1 and x1 equals c1x1. Thus, it can be ensured that the inventory holding expenses of the organization here are equal to the product of h1(x1 – d1). The focus is to create a positive inventory level at the end of the month. Hence, it can be procured that the total cost incurred during the first month is approximately c1x1 + h1(x1 − d1) (Djordjevic et al., 2019). The computation can be moved forward similarly for the upcoming twelve months as, XΣ12 j=1 cjxj ≡ c1x1 + c2x2 + . . . + c12x12 

 

 

Constraints

The production capacity for one month is: xj ≤ mj

And, as per the third assumption, shortage of inventory is not considered in the given hypothesis. Thus, the functional constraint will sum upto XΣj k=1 (xk − dk) ≥ 0.

LP Formulation and Sign Restrictions

The cost minimization is possible to the extent of :

XΣ12 j=1 cjxj + X 12 j=1 hj [ X j k=1 (xk − dk) , where xj ≤ mj for j = 1, 2, 3…,12 and xj ≥ 0 for j = 1, 2, 3…,12.

1. b) In the excel sheet.
2. c) Here, the purpose of the respective report is to present the sensitivity analysis of the proposed integer requirement of the production-planning program. The variables computed from the analysis will affect the decision-making procedure of the organization.

   The sensitive analysis here depends on the varied factors such as the limiting scope of resources provided by the organization (Gölzer, and Fritzsche, 2017). http://U25188 M452 Operations Management Assignment Sample

The determination of the most limiting resource used for the production planning will include an activity. This activity will forecast the capacity limitations of the resources based on the hours of production. Further, the resources for ensuring the holding capacity of the warehouses can also be computed from the activity. In other words, the inventory in stock and the capacity of resource holding can be determined by making the following assumptions:

Let us assume,

x1 = Number of cases of 1000 kgs of stainless steel

x2 = Number of cases of 500 grams of rusty protection.

Thus, the availability of the limiting resource changes is:

Maximum = 5×1 + 4.5×2

 

1. d) (i) Revised Production Planning Model

The production planning model proposed in the first activity has been revised in the following. Here, is the new formulation of the requisite inventory holding costs of the company. The objective of the sum is a critical analysis of the production indices.

As per the requirement of the production-planning problem, the purpose of the coursework is to draw an integer programming model for the production planning program, by scheduling the monthly production levels and all the complementary elements of the manufacturing process.

Here, we will denote j as the inner sum of the model function, i.e., Pj k=1(xk −dk). This will forecast the inventory level of the company during the first month of production. And hence, the computation of the distinct variables will impact the decision-making procedures of the management (Hueber et al., 2019). http://U25188 M452 Operations Management Assignment Sample

In the most simplistic approach, we can denote it as:

Minimize = XΣ12 j=1 cjxj + X 12 j=1 hjyj 

As mentioned above, j denotes the internal summation of the function.

(ii) Parametric analysis (in excel)

(iii) The limitations of the parametric analysis of production planning program are:

• The respective production planning leads to higher inventory level requirements during production, thus cost mitigation is very essential to be strategized (Vanzettiet al., 2018).http://U25188 M452 Operations Management Assignment Sample
• The process is critical and very complicated.
• The organization needs to keep a large holding capacity of inventory and stock because shortages of raw material can cause damage to the production cycle.
• The organization needs larger warehouses to stock a large quantity of inventory and raw materials.

Problem 3

Material Requirement Planning

1. Excel
2. To construct a low-level bill of material, a convenient order for the billing matrix is needed to be produced. For that, we need to make some assumptions as provided in the problem.

   Let us first consider a billing program for item 1 and item 2. Both are end-to-end products with required units of 100 units and 150 units for week 4 and week 8.

All the necessary components required here are:

First, item 1 demands one unit of item C, and two units of item A and.

Second, item 2 demands one unit of item B, one unit of item D, and three units of item E.

Third, item A demands one unit of item B and two units of item F.

Forth, item B demands one unit of item E and two units of item C.

Fifth, item C demands three units of item G, and one unit of item F and.

Lastly, item D demands one unit of item C and two units of item B.

The item requires resources in the following proportions and levels: 

Level 0: Items 1 and 2

Level 1: Items A and D.

Level 2: Item B

Level 3: Items C and E.

Level 4: Items F and G.

References

Aliyev, A.G. and Shahverdiyeva, R.O., 2018. Perspective directions of development of innovative structures on the basis of modern technologies. International Journal of Engineering and Manufacturing, 8(4), p.1.

Darmawan, A., Wong, H. and Thorstenson, A., 2018. Integration of promotion and production decisions in sales and operations planning. International Journal of Production Research, 56(12), pp.4186-4206.

Darvishi, F., Yaghin, R.G. and Sadeghi, A., 2020. Integrated fabric procurement and multi-site apparel production planning with cross-docking: a hybrid fuzzy-robust stochastic programming approach. Applied Soft Computing, 92, p.106267.

Djordjevic, I., Petrovic, D. and Stojic, G., 2019. A fuzzy linear programming model for aggregated production planning (APP) in the automotive industry. Computers in Industry, 110, pp.48-63.

Durante, M., Formisano, A., Viscusi, A. and Carrino, L., 2020. An innovative manufacturing method of aluminum foam sandwiches using a mesh-grid reinforcement as mold. The International Journal of Advanced Manufacturing Technology, 107(7), pp.3039-3048.

Foster, T., Norton, I. and Rahimifard, S., 2018. EPSRC Centre for Innovative Manufacturing in Food. Impact, 2018(6), pp.6-8.

Gölzer, P. and Fritzsche, A., 2017. Data-driven operations management: organisational implications of the digital transformation in industrial practice. Production Planning & Control, 28(16), pp.1332-1343.

Hueber, C., Fischer, G., Schwingshandl, N. and Schledjewski, R., 2019. Production planning optimisation for composite aerospace manufacturing. International Journal of Production Research, 57(18), pp.5857-5873.

Jamalnia, A., Yang, J.B., Xu, D.L., Feili, A. and Jamali, G., 2019. Evaluating the performance of aggregate production planning strategies under uncertainty in soft drink industry. Journal of Manufacturing Systems, 50, pp.146-162.

MacKenzie, I., 2019. Deliberate development of asset frontiers in innovative manufacturing businesses (Doctoral dissertation, University of York).

Rotella, G., Del Prete, A., Muzzupappa, M. and Umbrello, D., 2020. Innovative Manufacturing Process of Functionalized PA2200 for Reduced Adhesion Properties. Journal of Manufacturing and Materials Processing, 4(2), p.36.

Shinoda, K., Noda, H., Ohtomi, K., Yamada, T. and Akedo, J., 2019. Promotion of Knowledge and Technology Transfer Towards Innovative Manufacturing Process: Case Study of New Hybrid Coating Process. International Journal of Automation Technology, 13(3), pp.419-431.

Vanzetti, N., Broz, D., Corsano, G. and Montagna, J.M., 2018. An optimization approach for multiperiod production planning in a sawmill. Forest Policy and Economics, 97, pp.1-8.

Yelundur, V., 2017. Innovative manufacturing technologies for low-cost, high efficiency PERC-based PV modules (No. DOE-Suniva-7581). Suniva Inc., Norcross, GA (United States).