Cost accounting 202
Student Data
| ACT202 ASSIGNMENT DATA - SEMESTER 1 2018 | ||||||
| Student Number | 252967 | |||||
| Student Name | MR MD ASHRAFUL HAQUE (WFD) | |||||
| Instructions: | Enter your student number in the cell above (shaded Yellow) | |||||
| When you enter your student number you will generate the relevant data and figures necessary to complete your assignment. | ||||||
| These data and figures will be unique to your student number. Do NOT use figures generated for other student numbers. If you do you will be marked incorrect and possibly considered to have plagarised another student's work. | ||||||
| You cannot use this workbook, or link to this workbook to complete your assignment. You will need to print this worksheet and/or transcribe the data and figures manually. HINT!! If you print this worksheet to PDF format, you can "copy & paste" or "export" the details from the PDF document to an excel worksheet.[Select the right-click dropdown menu options, after selecting the text in the PDF document.] | ||||||
| SCROLL DOWN TO VIEW YOUR DATA | ||||||
| Heidegger Pty Ltd Case and Data Schedules | ||||||
| Heidegger Pty Ltd Case Background | ||||||
| Heidegger Pty Ltd produces anemometers used in the production of wind-powered electricity generating equipment. | ||||||
| The anemometers are sold to various engineering companies that produce wind-powered generators in Australia and Europe. | ||||||
| Projected sales in units for the coming four months are provided in the assignment data sheet. | ||||||
| The following data pertain to production policies and manufacturing specifications followed by Heidegger Pty Ltd._x000D_ The following details are provided in the assignment data sheet: | ||||||
| · Finished goods inventory on April 1. · The full absorption cost of the opening finished goods inventory. · The variable manufacturing cost of the opening finished goods inventory. · The desired finished goods ending inventory for each month. | ||||||
| · The data on materials used. · The amount of materials to be on hand at the beginning of the month · This stipulated amount of materials to be on hand at the beginning of the month is exactly the amount of material on hand on April 1. · (Assume that the material costs per unit are the same throughout the current quarter's production.) | ||||||
| · The direct labour used per unit of output. · The average direct labour cost per hour. | ||||||
| Details of the Overheads for each month are provided in the data list. The Overheads are estimated using a flexible budget formula. (Activity is measured in direct labour hours). You will have to determine the Maintenance cost and relevant statistical data necessary for you to do so is provided in the data List | ||||||
| Monthly selling and administrative overhead expenses are also estimated using a flexible budgeting formula. (Activity is measured in units sold.) Finance charges and bad debts are included in the figures provided and do not need to be identified separately in the selling and administrative overhead expenses. Details are provided in the data list. | ||||||
| Other information provided the assignment data list are: · The unit selling price of the anemometers. · The cost of land to be purchased in May. The company plans to purchase the land for future expansion. · The value and timing of dividends paid to shareholders. · Sales are on credit and the cash receipts pattern for each month is provided, as is the level of Accounts Receivable as at April 1. · Amounts not received in the month following the sale are written off as Bad Debts immediately. · The payment for labour and purchases of materials and other costs are for cash and paid for in the month of acquisition. · There is no Accounts Payable amount for this assignment. · The cash balance on April 1. | ||||||
| If the firm develops a cash shortage by the end of the month, sufficient cash is borrowed to cover the shortage (including any interest payments due). Any cash borrowed is repaid one month later, as is the interest due. The annual interest rate is provided with the assignment data. | ||||||
| During the process of preparing the organisation's budget, the sales manager is discussing the possible outcome of the forthcoming election with the production manager. She noted that if one of the major political parties wins the election and forms government, there is a strong possibility that alternative energy sources such as wind-powered electricity may no longer be as actively supported by the new government as is the case under the current government. | ||||||
| The sales manager's primary concern is that the current market for alternative power generation equipment is already volatile and subject to significant uncertainty. The production manager is also concerned about his plans to build the new highly automated manufacturing facility on the land to be purchased in May. This new manufacturing facility will enable him to manufacture, in-house, the major two parts he is now purchasing for assembly and to significantly automate the assembly process that is currently somewhat labour intensive. | ||||||
| His projections for the new facility indicate a reduction in direct material and direct labour costs of 33% but that his fixed manufacturing overheads are likely to increase by 65% due to the increased investment in production capacity. | ||||||
| Sales | Actual Sales Volume 3-months to June | |||||
| April | May | June | July | |||
| Units | 34,500 | 27,600 | 31,050 | 41,400 | 103,400 | |
| Unit selling price | $3,630 | |||||
| The desired finished goods ending inventory for each month is | 20% | of the next month's sales. | ||||
| The full absorption cost of the opening finished goods inventory is | $2,420 | per unit | ||||
| The variable manufacturing cost of the opening finished goods inventory is | $990 | per unit | ||||
| Finished goods inventory on April 1 is | 22,100 | units. | ||||
| Materials be on hand at the beginning of the month to produce | 60% | of that month's estimated sales. | ||||
| Direct Materials used per unit | Actual Materials Used - 3 Months to June | |||||
| Cups | Vanes | Cups | Vanes | |||
| Quantity | 2 | 3 | 157,700 | 34,900 | ||
| Actual Cost of Materials Used - 3 Months to June | ||||||
| Cost per unit | $41 | $55 | $7,758,840 | $4,332,020 | ||
| Actual Labour Used - 3 Months to June | ||||||
| Budgeted Direct Labour time per unit | 4 | (hrs.) | 272,320 | |||
| Actual Cost of Labour Used - 3 Months to June | ||||||
| Direct labour cost per hour | $20 | $6,263,400 | ||||
| Budgeted Manufacturing Overheads | Recent Statistical Data for Mainentance Costs | |||||
| Fixed Cost Component per month | Variable Cost Component per DL Hour | Labour Hrs | Total Maintenance Cost | |||
| Indirect Labour | $ - 0 | $28.98 | 665,900 | $40,848,000 | ||
| Power | $ - 0 | $2.76 | 759,000 | $44,367,000 | ||
| Maintenance | ??? | ??? | 696,900 | $42,021,000 | ||
| 634,800 | $39,675,000 | |||||
| Supervision | $19,320,000 | $0.00 | ||||
| Depreciation | $1,725,000 | $0.00 | ||||
| Rates and Utilities | $1,425,500 | $0.00 | ||||
| Other | $6,900,000 | $20.70 | ||||
| April | May | June | ||||
| Variable Selling Expenses | $18,785,250 | $15,028,200 | $16,906,725 | |||
| Fixed selling & admin expenses | $12,420,000 | $9,936,000 | $11,178,000 | |||
| Total selling & administrative expenses | $31,205,250 | $24,964,200 | $28,084,725 | |||
| Cash on hand at opening | $1,725,000 | |||||
| Annual Interest Rate on Borrowings | 8% | pa | ||||
| Cash from Sales | 0% | |||||
| Received in Month of Sale | 40% | |||||
| Received in Month After Sale | 58% | |||||
| Balance of Accounts Receivable at the start of the period | 0 | $79,900,000 | ||||
| Dividends Paid in May | $610,650 | |||||
| Land purchased in June | $17,940,000 | |||||
ACT202 - Assignment Details -
&P of &N
Callista Student List
| Person ID | Surname | Title | Given Names | Mark | Grade | Teach Period | Unit Code | Unit Location |
| 287459 | . | MISS | AMANDEEP KAUR | 1 2018 | ACT202 | MELB | ||
| 294207 | . | MS | ASHIMA KUMARI | 1 2018 | ACT202 | WFD | ||
| 275143 | . | MS | EKTA RANI | 1 2018 | ACT202 | MELB | ||
| 295834 | . | MISS | GURPREET KAUR | 1 2018 | ACT202 | MELB | ||
| 288773 | . | MISS | GURSIMRAN KAUR | 1 2018 | ACT202 | MELB | ||
| 287404 | . | MR | HARMANPREET SINGH | 1 2018 | ACT202 | MELB | ||
| 298346 | . | MR | HARSHPREET SINGH | 1 2018 | ACT202 | MELB | ||
| 283917 | . | MR | HUZAIFA | 1 2018 | ACT202 | WFD | ||
| 307731 | . | MR | LOVEPREET SINGH | 1 2018 | ACT202 | WFD | ||
| 291746 | . | MR | MANBRINDER SINGH | 1 2018 | ACT202 | MELB | ||
| 288270 | . | MR | MOHIT | 1 2018 | ACT202 | MELB | ||
| 310565 | . | MRS | PAWANDEEP KAUR | 1 2018 | ACT202 | WFD | ||
| 307620 | . | MR | RAVI | W | 1 2018 | ACT202 | WFD | |
| 299077 | ADHIKARI | MR | BIGYAN | 1 2018 | ACT202 | MELB | ||
| 294720 | AHMED | MR | IMTIAZ | 1 2018 | ACT202 | WFD | ||
| 288492 | ARORA | MR | ASHISH | 1 2018 | ACT202 | MELB | ||
| 271012 | BASNET | MS | PRATIKSHYA | 1 2018 | ACT202 | WFD | ||
| 278794 | BELL | MR | LACHLAN DANIEL JOSEPH | 1 2018 | ACT202 | EXT | ||
| 287954 | BENSEN | MS | CANDICE LEE | 1 2018 | ACT202 | WFD | ||
| 281846 | BHATTARAI | MR | PRASHANT | 1 2018 | ACT202 | SYDN | ||
| 297159 | BHATTARAI | MR | TEK NARAYAN | 1 2018 | ACT202 | MELB | ||
| 284868 | BUZON | MR | RAPHAEL KARLO | 1 2018 | ACT202 | WFD | ||
| 268238 | CHALISE | MR | BIBEK | 1 2018 | ACT202 | WFD | ||
| 300276 | CHITRAKAR | MISS | AKRITI | 1 2018 | ACT202 | WFD | ||
| 246574 | COXHILL | MRS | LAUREN MARIE | 1 2018 | ACT202 | EXT | ||
| 267044 | DALISTAN | MS | PRYNZES DAELYN | 1 2018 | ACT202 | WFD | ||
| 291844 | DARKER | MR | RYAN | 1 2018 | ACT202 | WFD | ||
| 289299 | DAS | MR | TUSHAR KUMAR | 1 2018 | ACT202 | WFD | ||
| 291146 | DESMOND | MISS | SAMANTHA JANE | 1 2018 | ACT202 | EXT | ||
| 296999 | DHAKAL | MR | PUKAR | 1 2018 | ACT202 | MELB | ||
| 295480 | DHIRANI | MR | ALI ARIF | 1 2018 | ACT202 | WFD | ||
| 113934 | DILLON | MRS | JESSICA LEE | 1 2018 | ACT202 | EXT | ||
| 286970 | DINH | MS | LAN HUONG | 1 2018 | ACT202 | MELB | ||
| 263876 | DONA | MS | RUSHANI IMALSHA GUNARATHNA | 1 2018 | ACT202 | MELB | ||
| 289498 | DUMARAOS | MR | JONATHAN | 1 2018 | ACT202 | WFD | ||
| 249724 | EROCIDO | MR | JOHN PAUL | W | 1 2018 | ACT202 | WFD | |
| 295865 | FERNANDO | MISS | MIKA | 1 2018 | ACT202 | WFD | ||
| 282942 | GASKELL | MR | JASON KARL | W | 1 2018 | ACT202 | EXT | |
| 286156 | GAUTAM | MISS | LEENA | 1 2018 | ACT202 | MELB | ||
| 272986 | GHIMIRE | MR | NIKESH | 1 2018 | ACT202 | WFD | ||
| 294188 | GIRI | MISS | GARIMA | 1 2018 | ACT202 | SYDN | ||
| 283279 | GIRI | MISS | KAJOL | 1 2018 | ACT202 | SYDN | ||
| 179647 | GLACKIN | MR | KEVIN | W | 1 2018 | ACT202 | EXT | |
| 266860 | GREGORY | MS | KATRINA JOY | W | 1 2018 | ACT202 | EXT | |
| 269369 | GURUNG | MS | PRATIMA | 1 2018 | ACT202 | WFD | ||
| 278433 | HALKITIS | MR | MIHALIS | 1 2018 | ACT202 | WFD | ||
| 296022 | HAMAL | MR | RAHUL | W | 1 2018 | ACT202 | SYDN | |
| 252967 | HAQUE | MR | MD ASHRAFUL | 1 2018 | ACT202 | WFD | ||
| 301153 | HARPER | MR | BLAKE | 1 2018 | ACT202 | WFD | ||
| 148173 | HEIGHT | MR | NEIL ANDREW | 1 2018 | ACT202 | WFD | ||
| 307877 | HOANG | MR | QUOC TUAN | W | 1 2018 | ACT202 | WFD | |
| 300011 | HURLEY | MISS | REBECCA | 1 2018 | ACT202 | EXT | ||
| 288126 | HYLAND | MR | DOUGLAS CHRISTOPHER | 1 2018 | ACT202 | EXT | ||
| 301450 | JONES | MS | GEORGIA CLARE | W | 1 2018 | ACT202 | WFD | |
| 301776 | K C | MR | PRAFULLA | 1 2018 | ACT202 | WFD | ||
| 280145 | K C | MR | PRAGYAN | 1 2018 | ACT202 | WFD | ||
| 293651 | KAFLE | MR | SACHIT | 1 2018 | ACT202 | SYDN | ||
| 287391 | KALPONA | MS | UMMAY HANI | 1 2018 | ACT202 | WFD | ||
| 270603 | KANDEL | MR | BIPLAV | 1 2018 | ACT202 | WFD | ||
| 287991 | KATNA | MR | NIKHIL | 1 2018 | ACT202 | MELB | ||
| 287699 | KAUR | MISS | SARVJEET | 1 2018 | ACT202 | MELB | ||
| 289737 | KEARIE | MISS | EUNICE NJERI | 1 2018 | ACT202 | WFD | ||
| 282304 | KHADKA | MR | SANGAM | 1 2018 | ACT202 | SYDN | ||
| 300605 | KHARAL | MR | SAKAR | 1 2018 | ACT202 | WFD | ||
| 300709 | KHATRI | MR | AMARLAL | 1 2018 | ACT202 | WFD | ||
| 266241 | KOSMA | MISS | ANNA | 1 2018 | ACT202 | EXT | ||
| 301222 | LAI | MISS | NETANYA | 1 2018 | ACT202 | WFD | ||
| 312286 | LE | MS | THI BICH TRAN | 1 2018 | ACT202 | MELB | ||
| 275937 | LI | MR | MENGLONG | 1 2018 | ACT202 | WFD | ||
| 302049 | LINGAD | MS | LYKA JHAINE OCAMPO | 1 2018 | ACT202 | WFD | ||
| 267918 | MACDONALD | MR | MICHAEL KIYOSHI | 1 2018 | ACT202 | WFD | ||
| 287631 | MAHARJAN | MR | AAYUSH | 1 2018 | ACT202 | SYDN | ||
| 301658 | MAHARJAN | MISS | SWETA | 1 2018 | ACT202 | WFD | ||
| 301097 | MALADY | MISS | JESSICA ISOBEL | 1 2018 | ACT202 | WFD | ||
| 286836 | MAQSOOD | MR | TAYYAB | 1 2018 | ACT202 | MELB | ||
| 301113 | MOUSELLIS | MISS | MARIA | 1 2018 | ACT202 | WFD | ||
| 302048 | MU | MS | KRISTINA | 1 2018 | ACT202 | WFD | ||
| 272474 | MUNYOKI | MR | LEE NGIE | 1 2018 | ACT202 | WFD | ||
| 267674 | NAIR | MR | LACHLAN | 1 2018 | ACT202 | WFD | ||
| 265573 | NAMBIRI | MR | NAMBIRI | W | 1 2018 | ACT202 | EXT | |
| 294537 | NEUPANE | MR | AASHISH | 1 2018 | ACT202 | WFD | ||
| 245344 | ONI | MR | TOUSHIK AZAD | 1 2018 | ACT202 | WFD | ||
| 299752 | OSHIN | MR | ABDUL RAKIB | 1 2018 | ACT202 | WFD | ||
| 292635 | PAIJA PUN | MR | SUJAN | 1 2018 | ACT202 | WFD | ||
| 204386 | PAN | MRS | ZHIFEI | 1 2018 | ACT202 | EXT | ||
| 295719 | PANGENI | MR | BHUWAN | 1 2018 | ACT202 | SYDN | ||
| 279930 | PASTOR | MR | JOB MARC ANGELO | 1 2018 | ACT202 | WFD | ||
| 282571 | PATEL | MR | HARDIKBHAI SURESHBHAI | 1 2018 | ACT202 | WFD | ||
| 295770 | PAUDEL | MISS | ASHWEETA | 1 2018 | ACT202 | SYDN | ||
| 301098 | PERRY | MR | JARROD CONNOR | 1 2018 | ACT202 | WFD | ||
| 135983 | PICKERING | MS | DIEDRE MAY | 1 2018 | ACT202 | EXT | ||
| 296500 | POVEDA ALFONSO | MR | BENJAMIN | 1 2018 | ACT202 | WFD | ||
| 301093 | QUIJANO | MR | RONALD VINCENT | 1 2018 | ACT202 | WFD | ||
| 287244 | RANASINGHAGE | MR | RUWAN CHAMARA | 1 2018 | ACT202 | WFD | ||
| 278245 | ROSAL | MS | DAYANARA FLORES | 1 2018 | ACT202 | WFD | ||
| 297757 | SAFFOON | MRS | SADIA | 1 2018 | ACT202 | WFD | ||
| 297580 | SAPKOTA | MR | POSHAK | 1 2018 | ACT202 | WFD | ||
| 271390 | SAPKOTA | MR | ROSHAN | 1 2018 | ACT202 | WFD | ||
| 283647 | SAZEED | MR | MUHAMMAD TOUSIF | 1 2018 | ACT202 | WFD | ||
| 301483 | SHARMA | MISS | ADITI | 1 2018 | ACT202 | MELB | ||
| 301775 | SITOULA | MR | SOURAV | 1 2018 | ACT202 | SYDN | ||
| 287354 | SKELLEY | MISS | ALLISON JOHANNA | 1 2018 | ACT202 | EXT | ||
| 290204 | SOK | MR | POV | 1 2018 | ACT202 | WFD | ||
| 205354 | SONNTAG | MRS | KELLY | W | 1 2018 | ACT202 | EXT | |
| 297323 | SUDIRIKKU HENNADIGE | MISS | UMAYANGANI SHASHIKALA HENNADIGE | 1 2018 | ACT202 | WFD | ||
| 294788 | SUN | MR | XIANG | 1 2018 | ACT202 | WFD | ||
| 300610 | SUNG | MR | YEON SEO | 1 2018 | ACT202 | WFD | ||
| 300582 | TAMANG | MISS | SHANTI | 1 2018 | ACT202 | SYDN | ||
| 991108 | TUCKER | MRS | SHARON LOUISE | W | 1 2018 | ACT202 | EXT | |
| 272971 | UPRETI | MR | DIPIT | 1 2018 | ACT202 | SYDN | ||
| 301095 | VARGAS | MR | CHARLES KENDRIC | 1 2018 | ACT202 | WFD | ||
| 196758 | WATSON | MR | THOREN ALEX | 1 2018 | ACT202 | WFD | ||
| 231824 | WU | MR | ZIPING | 1 2018 | ACT202 | WFD | ||
| 255477 | YU | MS | SUYEONG | 1 2018 | ACT202 | SYDN | ||
| 294986 | ZHANG | MRS | QIANWEN | 1 2018 | ACT202 | EXT |
Student_List
| Student List | Student Number Mod Index | 3 | 4 | 6 | Student Number Index | ||||
| 287459 | MISS AMANDEEP KAUR . | MELB | 35 | 3 | 4 | 2 | 65% | 55 | |
| 294207 | MS ASHIMA KUMARI . | WFD | 24 | 1 | 1 | 1 | 76% | 42 | |
| 275143 | MS EKTA RANI . | MELB | 22 | 2 | 3 | 1 | 78% | 36 | |
| 295834 | MISS GURPREET KAUR . | MELB | 31 | 2 | 4 | 4 | 131% | 51 | |
| 288773 | MISS GURSIMRAN KAUR . | MELB | 35 | 3 | 4 | 3 | 65% | 56 | |
| 287404 | MR HARMANPREET SINGH . | MELB | 25 | 2 | 2 | 6 | 125% | 47 | |
| 298346 | MR HARSHPREET SINGH . | MELB | 32 | 3 | 1 | 6 | 132% | 53 | |
| 283917 | MR HUZAIFA . | WFD | 30 | 1 | 3 | 1 | 70% | 42 | |
| 307731 | MR LOVEPREET SINGH . | WFD | 21 | 1 | 2 | 6 | 79% | 41 | |
| 291746 | MR MANBRINDER SINGH . | MELB | 29 | 3 | 2 | 3 | 129% | 50 | |
| 288270 | MR MOHIT . | MELB | 27 | 1 | 4 | 2 | 127% | 37 | |
| 310565 | MRS PAWANDEEP KAUR . | WFD | 20 | 3 | 1 | 5 | 80% | 40 | |
| 307620 | MR RAVI . | WFD | 18 | 1 | 3 | 4 | 118% | 27 | |
| 299077 | MR BIGYAN ADHIKARI | MELB | 34 | 2 | 3 | 5 | 66% | 52 | |
| 294720 | MR IMTIAZ AHMED | WFD | 24 | 1 | 1 | 4 | 124% | 39 | |
| 288492 | MR ASHISH ARORA | MELB | 33 | 1 | 2 | 1 | 133% | 48 | |
| 271012 | MS PRATIKSHYA BASNET | WFD | 13 | 2 | 2 | 4 | 113% | 33 | |
| 278794 | MR LACHLAN DANIEL JOSEPH BELL | EXT | 37 | 2 | 2 | 1 | 137% | 66 | |
| 287954 | MS CANDICE LEE BENSEN | WFD | 35 | 3 | 4 | 3 | 135% | 56 | |
| 281846 | MR PRASHANT BHATTARAI | SYDN | 29 | 3 | 2 | 3 | 129% | 50 | |
| 297159 | MR TEK NARAYAN BHATTARAI | MELB | 33 | 1 | 2 | 4 | 67% | 57 | |
| 284868 | MR RAPHAEL KARLO BUZON | WFD | 36 | 1 | 1 | 5 | 136% | 58 | |
| 268238 | MR BIBEK CHALISE | WFD | 29 | 3 | 2 | 4 | 129% | 45 | |
| 300276 | MISS AKRITI CHITRAKAR | WFD | 18 | 1 | 3 | 4 | 118% | 39 | |
| 246574 | MRS LAUREN MARIE COXHILL | EXT | 28 | 2 | 1 | 5 | 128% | 52 | |
| 267044 | MS PRYNZES DAELYN DALISTAN | WFD | 23 | 3 | 4 | 2 | 123% | 49 | |
| 291844 | MR RYAN DARKER | WFD | 28 | 2 | 1 | 1 | 128% | 42 | |
| 289299 | MR TUSHAR KUMAR DAS | WFD | 39 | 1 | 4 | 5 | 61% | 58 | |
| 291146 | MISS SAMANTHA JANE DESMOND | EXT | 23 | 3 | 4 | 2 | 123% | 49 | |
| 296999 | MR PUKAR DHAKAL | MELB | 44 | 3 | 1 | 6 | 56% | 59 | |
| 295480 | MR ALI ARIF DHIRANI | WFD | 28 | 2 | 1 | 6 | 128% | 47 | |
| 113934 | MRS JESSICA LEE DILLON | EXT | 21 | 1 | 2 | 2 | 121% | 43 | |
| 286970 | MS LAN HUONG DINH | MELB | 32 | 3 | 1 | 2 | 132% | 49 | |
| 263876 | MS RUSHANI IMALSHA GUNARATHNA DONA | MELB | 32 | 3 | 1 | 1 | 132% | 66 | |
| 289498 | MR JONATHAN DUMARAOS | WFD | 40 | 2 | 1 | 1 | 140% | 60 | |
| 249724 | MR JOHN PAUL EROCIDO | WFD | 28 | 2 | 1 | 1 | 128% | 48 | |
| 295865 | MISS MIKA FERNANDO | WFD | 35 | 3 | 4 | 6 | 65% | 53 | |
| 282942 | MR JASON KARL GASKELL | EXT | 27 | 1 | 4 | 1 | 127% | 48 | |
| 286156 | MISS LEENA GAUTAM | MELB | 28 | 2 | 1 | 4 | 128% | 45 | |
| 272986 | MR NIKESH GHIMIRE | WFD | 34 | 2 | 3 | 4 | 134% | 51 | |
| 294188 | MISS GARIMA GIRI | SYDN | 32 | 3 | 1 | 1 | 132% | 48 | |
| 283279 | MISS KAJOL GIRI | SYDN | 31 | 2 | 4 | 5 | 69% | 46 | |
| 179647 | MR KEVIN GLACKIN | EXT | 34 | 2 | 3 | 3 | 66% | 50 | |
| 266860 | MS KATRINA JOY GREGORY | EXT | 28 | 2 | 1 | 3 | 128% | 50 | |
| 269369 | MS PRATIMA GURUNG | WFD | 35 | 3 | 4 | 5 | 65% | 52 | |
| 278433 | MR MIHALIS HALKITIS | WFD | 27 | 1 | 4 | 5 | 73% | 46 | |
| 296022 | MR RAHUL HAMAL | SYDN | 21 | 1 | 2 | 6 | 121% | 35 | |
| 252967 | MR MD ASHRAFUL HAQUE | WFD | 31 | 2 | 4 | 4 | 69% | 51 | |
| 301153 | MR BLAKE HARPER | WFD | 13 | 2 | 2 | 5 | 87% | 28 | |
| 148173 | MR NEIL ANDREW HEIGHT | WFD | 24 | 1 | 1 | 4 | 76% | 45 | |
| 307877 | MR QUOC TUAN HOANG | WFD | 32 | 3 | 1 | 3 | 68% | 50 | |
| 300011 | MISS REBECCA HURLEY | EXT | 5 | 3 | 2 | 1 | 95% | 24 | |
| 288126 | MR DOUGLAS CHRISTOPHER HYLAND | EXT | 27 | 1 | 4 | 3 | 127% | 56 | |
| 301450 | MS GEORGIA CLARE JONES | WFD | 13 | 2 | 2 | 6 | 113% | 35 | |
| 301776 | MR PRAFULLA K C | WFD | 24 | 1 | 1 | 4 | 124% | 39 | |
| 280145 | MR PRAGYAN K C | WFD | 20 | 3 | 1 | 5 | 80% | 34 | |
| 293651 | MR SACHIT KAFLE | SYDN | 26 | 3 | 3 | 6 | 74% | 41 | |
| 287391 | MS UMMAY HANI KALPONA | WFD | 30 | 1 | 3 | 4 | 70% | 51 | |
| 270603 | MR BIPLAV KANDEL | WFD | 18 | 1 | 3 | 5 | 82% | 34 | |
| 287991 | MR NIKHIL KATNA | MELB | 36 | 1 | 1 | 4 | 64% | 51 | |
| 287699 | MISS SARVJEET KAUR | MELB | 41 | 3 | 2 | 6 | 59% | 59 | |
| 289737 | MISS EUNICE NJERI KEARIE | WFD | 36 | 1 | 1 | 1 | 64% | 60 | |
| 282304 | MR SANGAM KHADKA | SYDN | 19 | 2 | 4 | 6 | 119% | 35 | |
| 300605 | MR SAKAR KHARAL | WFD | 14 | 3 | 3 | 6 | 86% | 29 | |
| 300709 | MR AMARLAL KHATRI | WFD | 19 | 2 | 4 | 1 | 81% | 36 | |
| 266241 | MISS ANNA KOSMA | EXT | 21 | 1 | 2 | 1 | 79% | 36 | |
| 301222 | MISS NETANYA LAI | WFD | 10 | 2 | 3 | 3 | 110% | 26 | |
| 312286 | MS THI BICH TRAN LE | MELB | 22 | 2 | 3 | 6 | 122% | 41 | |
| 275937 | MR MENGLONG LI | WFD | 33 | 1 | 2 | 6 | 67% | 47 | |
| 302049 | MS LYKA JHAINE OCAMPO LINGAD | WFD | 18 | 1 | 3 | 5 | 82% | 46 | |
| 267918 | MR MICHAEL KIYOSHI MACDONALD | WFD | 33 | 1 | 2 | 2 | 133% | 61 | |
| 287631 | MR AAYUSH MAHARJAN | SYDN | 27 | 1 | 4 | 4 | 73% | 45 | |
| 301658 | MISS SWETA MAHARJAN | WFD | 23 | 3 | 4 | 1 | 123% | 42 | |
| 301097 | MISS JESSICA ISOBEL MALADY | WFD | 20 | 3 | 1 | 5 | 80% | 46 | |
| 286836 | MR TAYYAB MAQSOOD | MELB | 33 | 1 | 2 | 3 | 133% | 50 | |
| 301113 | MISS MARIA MOUSELLIS | WFD | 9 | 1 | 2 | 6 | 91% | 29 | |
| 302048 | MS KRISTINA MU | WFD | 17 | 3 | 2 | 2 | 117% | 31 | |
| 272474 | MR LEE NGIE MUNYOKI | WFD | 26 | 3 | 3 | 4 | 126% | 45 | |
| 267674 | MR LACHLAN NAIR | WFD | 32 | 3 | 1 | 6 | 132% | 47 | |
| 265573 | MR NAMBIRI NAMBIRI | EXT | 28 | 2 | 1 | 5 | 72% | 46 | |
| 294537 | MR AASHISH NEUPANE | WFD | 30 | 1 | 3 | 1 | 70% | 48 | |
| 245344 | MR TOUSHIK AZAD ONI | WFD | 22 | 2 | 3 | 6 | 122% | 41 | |
| 299752 | MR ABDUL RAKIB OSHIN | WFD | 34 | 2 | 3 | 1 | 134% | 54 | |
| 292635 | MR SUJAN PAIJA PUN | WFD | 27 | 1 | 4 | 4 | 73% | 45 | |
| 204386 | MRS ZHIFEI PAN | EXT | 23 | 3 | 4 | 2 | 123% | 37 | |
| 295719 | MR BHUWAN PANGENI | SYDN | 33 | 1 | 2 | 3 | 67% | 50 | |
| 279930 | MR JOB MARC ANGELO PASTOR | WFD | 30 | 1 | 3 | 2 | 130% | 55 | |
| 282571 | MR HARDIKBHAI SURESHBHAI PATEL | WFD | 25 | 2 | 2 | 2 | 75% | 55 | |
| 295770 | MISS ASHWEETA PAUDEL | SYDN | 30 | 1 | 3 | 3 | 130% | 50 | |
| 301098 | MR JARROD CONNOR PERRY | WFD | 21 | 1 | 2 | 2 | 121% | 43 | |
| 135983 | MS DIEDRE MAY PICKERING | EXT | 29 | 3 | 2 | 5 | 71% | 52 | |
| 296500 | MR BENJAMIN POVEDA ALFONSO | WFD | 22 | 2 | 3 | 1 | 122% | 48 | |
| 301093 | MR RONALD VINCENT QUIJANO | WFD | 16 | 2 | 1 | 6 | 84% | 41 | |
| 287244 | MR RUWAN CHAMARA RANASINGHAGE | WFD | 27 | 1 | 4 | 3 | 127% | 56 | |
| 278245 | MS DAYANARA FLORES ROSAL | WFD | 28 | 2 | 1 | 5 | 72% | 52 | |
| 297757 | MRS SADIA SAFFOON | WFD | 37 | 2 | 2 | 1 | 63% | 54 | |
| 297580 | MR POSHAK SAPKOTA | WFD | 31 | 2 | 4 | 1 | 131% | 48 | |
| 271390 | MR ROSHAN SAPKOTA | WFD | 22 | 2 | 3 | 4 | 122% | 39 | |
| 283647 | MR MUHAMMAD TOUSIF SAZEED | WFD | 30 | 1 | 3 | 2 | 70% | 55 | |
| 301483 | MISS ADITI SHARMA | MELB | 19 | 2 | 4 | 1 | 81% | 36 | |
| 301775 | MR SOURAV SITOULA | SYDN | 23 | 3 | 4 | 5 | 77% | 40 | |
| 287354 | MISS ALLISON JOHANNA SKELLEY | EXT | 29 | 3 | 2 | 4 | 129% | 57 | |
| 290204 | MR POV SOK | WFD | 17 | 3 | 2 | 4 | 117% | 27 | |
| 205354 | MRS KELLY SONNTAG | EXT | 19 | 2 | 4 | 1 | 119% | 36 | |
| 297323 | MISS UMAYANGANI SHASHIKALA HENNADIGE SUDIRIKKU HENNADIGE | WFD | 26 | 3 | 3 | 5 | 74% | 82 | |
| 294788 | MR XIANG SUN | WFD | 38 | 3 | 3 | 3 | 138% | 50 | |
| 300610 | MR YEON SEO SUNG | WFD | 10 | 2 | 3 | 3 | 110% | 26 | |
| 300582 | MISS SHANTI TAMANG | SYDN | 18 | 1 | 3 | 1 | 118% | 36 | |
| 991108 | MRS SHARON LOUISE TUCKER | EXT | 28 | 2 | 1 | 5 | 128% | 52 | |
| 272971 | MR DIPIT UPRETI | SYDN | 28 | 2 | 1 | 2 | 72% | 43 | |
| 301095 | MR CHARLES KENDRIC VARGAS | WFD | 18 | 1 | 3 | 2 | 82% | 43 | |
| 196758 | MR THOREN ALEX WATSON | WFD | 36 | 1 | 1 | 4 | 136% | 57 | |
| 231824 | MR ZIPING WU | WFD | 20 | 3 | 1 | 3 | 120% | 32 | |
| 255477 | MS SUYEONG YU | SYDN | 30 | 1 | 3 | 2 | 70% | 43 | |
| 294986 | MRS QIANWEN ZHANG | EXT | 38 | 3 | 3 | 2 | 138% | 55 | |
| 0 | 0 | 0 | 1 | 1 | 3 | 100% | 2 | ||
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| 0 | 0 | 0 | 1 | 1 | 3 | 100% | 2 | ||
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| 0 | 0 | 0 | 1 | 1 | 3 | 100% | 2 | ||
| 0 | 0 | 0 | 1 | 1 | 3 | 100% | 2 | ||
| 999990 | TRIAL STUDENT 1 | YYY | 45 | 1 | 2 | 1 | 145% | 60 | |
| 999991 | TRIAL STUDENT 2 | XXX | 46 | 2 | 3 | 2 | 54% | 61 | |
| 999992 | TRIAL STUDENT 3 | YYY | 47 | 3 | 4 | 3 | 147% | 62 | |
| 999993 | TRIAL STUDENT 4 | XXX | 48 | 1 | 1 | 4 | 52% | 63 | |
| 999994 | TRIAL STUDENT 5 | YYY | 49 | 2 | 2 | 5 | 149% | 64 | |
| 999995 | TRIAL STUDENT 6 | XXX | 50 | 3 | 3 | 6 | 50% | 65 | |
| 999996 | TRIAL STUDENT 7 | YYY | 51 | 1 | 4 | 1 | 151% | 66 | |
| 999997 | TRIAL STUDENT 8 | XXX | 52 | 2 | 1 | 2 | 48% | 67 | |
| 999998 | TRIAL STUDENT 9 | YYY | 53 | 3 | 2 | 3 | 153% | 68 | |
| 999999 | TRIAL STUDENT 10 | XXX | 54 | 1 | 3 | 5 | 46% | 70 |
Original Data
| Sales | ||||||||
| January | February | March | april | |||||
| Units | 50,000 | 40,000 | 45,000 | 60,000 | ||||
| Unit selling price | $4,300 | |||||||
| The desired finished goods ending inventory for each month is | 40% | of the next month's sales. | varies around 40% based on student number | |||||
| The full absorption cost of the opening finished goods inventory is | $ 3,500 | per unit | ||||||
| The variable manufacturing cost of the opening finished goods inventory is | $ 1,430 | |||||||
| Finished goods inventory on January 1 is | 32,000 | |||||||
| Materials be on hand at the beginning of the month to produce | 40% | of that month's estimated sales. | varies around 40% based on student number | |||||
| Direct Materials used per unit | Actual Materials Used - 3 Months to March | |||||||
| Part 714 | Part 502 | Part 714 | Part 502 | |||||
| Quantity | 3 | 4 | 342,900 | 67,500 | varies based on student number | |||
| Cost per unit | $60 | $80 | Actual Cost of Materials Used - 3 Months to March | |||||
| $24,688,800 | $13,784,580 | varies based on student number | ||||||
| Actual LabourUsed - 3 Months to March | ||||||||
| Direct labor time per unit | 6 | (hrs.) | 592,340 | varies based on student number | ||||
| Direct labor cost per hour | $35 | Actual Cost of Labour Used - 3 Months to March | ||||||
| $27,247,600 | varies based on student number | |||||||
| Manufacturing Overheads | ||||||||
| Fixed Cost Component | Variable Cost Component | Recent Statistical Data for Mainentance Costs | ||||||
| Indirect Labour | $ 42.00 | Labour Hrs | Total Maintenance Cost | |||||
| Power | $ 4.00 | 965,000 | $59,200,000 | |||||
| Maintenance | $ 22,742,000 | $ 37.78 | 1,100,000 | $64,300,000 | ||||
| Supervision | $ 28,000,000 | 1,010,000 | $60,900,000 | |||||
| Depreciation | $ 2,500,000 | 920,000 | $57,500,000 | |||||
| Rates and Utilities | $ 2,066,000 | |||||||
| Other | $ 10,000,000 | $ 30.00 | ||||||
| January | February | March | ||||||
| Variable Selling Expenses | $ 32,250,000 | $ 25,800,000 | $ 29,025,000 | |||||
| Fixed selling & admin expenses | $ 18,000,000 | $ 14,400,000 | $ 16,200,000 | |||||
| Total selling & administrative expenses | $ 50,250,000 | $ 40,200,000 | $ 45,225,000 | |||||
| Cash on hand at opening | $ 2,500,000 | |||||||
| Annual Interest Rate on Borrowings | 6% | pa | ||||||
| Cash from Sales | ||||||||
| Received in Month of Sale | 20% | |||||||
| Received in Month After Sale | 78% | |||||||
| Balance of Accounts Receivable at the start of the period | $184,470,000 | |||||||
| Dividends Paid in January | $885,000 | |||||||
| Land purchased in February | $26,000,000 |
Data_Sheet
| Hide this section | Password big ----------------> | |||||||||||||||
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CDU: cell and text are white to confuse the unwary click on cell to see the password in the formula bar | Password ord ----------------> | |||||||||||||||
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CDU: cell and text are white to confuse the unwary click on cell to see the password in the formula bar | Worksheets Names | Select Base Number Index of 1 | FALSE | |||||||||||||
| Student Data | Student_Number_Mod_Index | 2 | 4 | 4 | ||||||||||||
| 1 | Case Details01 | Wittgenstein Pty Ltd | Student_Number_Even | FALSE | ||||||||||||
| 2 | Case Details02 | Krishnamurti Pty Ltd | Student_Number_Schd | Production | ||||||||||||
| 3 | Case Details03 | Weiming Pty Ltd | Student_Number_Bus_name | Heidegger Pty Ltd | ||||||||||||
| 4 | Case Details04 | Heidegger Pty Ltd | Student_Number_Case | Case Details04 | ||||||||||||
| 5 | Case Details05 | Schopenhauer Pty Ltd | Student_Number_Index | 69% | ||||||||||||
| 6 | Case Details06 | Shariati Pty Ltd | Student_Cost_Sheet | 2 | ||||||||||||
| Student_Quarter | Qtr4 | |||||||||||||||
| 1 | Sales | Sch01 | Business_names | |||||||||||||
| 2 | Production | Sch02 | 1 | Wittgenstein Pty Ltd | ||||||||||||
| 3 | Direct Materials | Sch03 | 2 | Krishnamurti Pty Ltd | ||||||||||||
| 4 | Direct Labour | Sch04 | 3 | Weiming Pty Ltd | ||||||||||||
| 5 | Overhead | Sch05 | 4 | Heidegger Pty Ltd | ||||||||||||
| 6 | Selling & Admin | Sch06 | 5 | Schopenhauer Pty Ltd | ||||||||||||
| 7 | Ending Finished Goods | Sch07 | 6 | Shariati Pty Ltd | ||||||||||||
| 8 | Cost of Goods Sold | Sch08 | Part_name | Part01 | Part02 | |||||||||||
| 9 | Income Statement | Sch09 | 1 | Shaft | Bearing | |||||||||||
| 10 | Cash Budget | Sch10 | 2 | Capacitor | Switch | |||||||||||
| 11 | Sales Costs | Sch11 | 3 | Rotor | Blades | |||||||||||
| 4 | Cups | Vanes | ||||||||||||||
| Qtr1 | June | July | August | September | October | 5 | Fuse | Isolator | ||||||||
| Qtr2 | September | October | November | December | January | 6 | Bearing | Caseing | ||||||||
| Qtr3 | December | January | February | March | April | Energy_type | Type01 | Component | ||||||||
| Qtr4 | March | April | May | June | July | 1 | wind-powered | propellers | ||||||||
| 2 | solar-powered | AC/DC Switches | ||||||||||||||
| Actual Sales Change | 11% | 3 | hydro-powered | turbines | ||||||||||||
| Actual Usage Change Part01 | 12% | 4 | wind-powered | anemometers | ||||||||||||
| Actual Usage Change Part02 | 13% | 5 | solar-powered | batteries | ||||||||||||
| Actual Cost Change Part01 | 20% | 6 | hydro-powered | turbines | ||||||||||||
| Actual Cost Change Part02 | 33% | |||||||||||||||
| Actual Labour Usage Change | 24% | |||||||||||||||
| Actual Labour Cost Change | 15% | |||||||||||||||
| Selling Price Constant | 3000 | |||||||||||||||
| CVP_Var_Cost_Change | 33% | |||||||||||||||
| CVP_Fixed_Cost_Change | 65% | |||||||||||||||
| Working Parameters | ||||||||||||||||
| A4 | B4 | C4 | D4 | E4 | F4 | G4 | H4 | I4 | ||||||||
| A5 | B5 | C5 | D5 | E5 | F5 | G5 | H5 | I5 | ||||||||
| A6 | B6 | C6 | D6 | E6 | F6 | G6 | H6 | I6 | ||||||||
| A7 | B7 | C7 | D7 | E7 | F7 | G7 | H7 | I7 | ||||||||
| A8 | B8 | C8 | D8 | E8 | F8 | G8 | H8 | I8 | ||||||||
| A9 | B9 | C9 | D9 | E9 | F9 | G9 | H9 | I9 | ||||||||
| A10 | B10 | C10 | D10 | E10 | F10 | G10 | H10 | I10 | ||||||||
| A11 | B11 | C11 | D11 | E11 | F11 | G11 | H11 | I11 | ||||||||
| A12 | B12 | C12 | D12 | E12 | F12 | G12 | H12 | I12 | ||||||||
| A13 | B13 | C13 | D13 | E13 | F13 | G13 | H13 | I13 | ||||||||
| A14 | B14 | C14 | D14 | E14 | F14 | G14 | H14 | I14 | ||||||||
| A15 | B15 | C15 | D15 | E15 | F15 | G15 | H15 | I15 | ||||||||
| A16 | B16 | C16 | D16 | E16 | F16 | G16 | H16 | I16 | ||||||||
| A17 | B17 | C17 | D17 | E17 | F17 | G17 | H17 | I17 | ||||||||
| A18 | B18 | C18 | D18 | E18 | F18 | G18 | H18 | I18 | ||||||||
| A19 | B19 | C19 | D19 | E19 | F19 | G19 | H19 | I19 | ||||||||
| A20 | B20 | C20 | D20 | E20 | F20 | G20 | H20 | I20 | ||||||||
| A21 | B21 | C21 | D21 | E21 | F21 | G21 | H21 | I21 | ||||||||
| A22 | B22 | C22 | D22 | E22 | F22 | G22 | H22 | I22 | ||||||||
| A23 | B23 | C23 | D23 | E23 | F23 | G23 | H23 | I23 | ||||||||
| A24 | B24 | C24 | D24 | E24 | F24 | G24 | H24 | I24 | ||||||||
| A25 | B25 | C25 | D25 | E25 | F25 | G25 | H25 | I25 | ||||||||
| A26 | B26 | C26 | D26 | E26 | F26 | G26 | H26 | I26 | ||||||||
| A27 | B27 | C27 | D27 | E27 | F27 | G27 | H27 | I27 | ||||||||
| A28 | B28 | C28 | D28 | E28 | F28 | G28 | H28 | I28 | ||||||||
| A29 | B29 | C29 | D29 | E29 | F29 | G29 | H29 | I29 | ||||||||
| A30 | B30 | C30 | D30 | E30 | F30 | G30 | H30 | I30 | ||||||||
| A31 | B31 | C31 | D31 | E31 | F31 | G31 | H31 | I31 | ||||||||
| A32 | B32 | C32 | D32 | E32 | F32 | G32 | H32 | I32 | ||||||||
| A33 | B33 | C33 | D33 | E33 | F33 | G33 | H33 | I33 | ||||||||
| A34 | B34 | C34 | D34 | E34 | F34 | G34 | H34 | I34 | ||||||||
| A35 | B35 | C35 | D35 | E35 | F35 | G35 | H35 | I35 | ||||||||
| A36 | B36 | C36 | D36 | E36 | F36 | G36 | H36 | I36 | ||||||||
| A37 | B37 | C37 | D37 | E37 | F37 | G37 | H37 | I37 | ||||||||
| A38 | B38 | C38 | D38 | E38 | F38 | G38 | H38 | I38 | ||||||||
| A39 | B39 | C39 | D39 | E39 | F39 | G39 | H39 | I39 | ||||||||
| A40 | B40 | C40 | D40 | E40 | F40 | G40 | H40 | I40 | ||||||||
| A41 | B41 | C41 | D41 | E41 | F41 | G41 | H41 | I41 | ||||||||
| A42 | B42 | C42 | D42 | E42 | F42 | G42 | H42 | I42 | ||||||||
| A43 | B43 | C43 | D43 | E43 | F43 | G43 | H43 | I43 | ||||||||
| A44 | B44 | C44 | D44 | E44 | F44 | G44 | H44 | I44 | ||||||||
| A45 | B45 | C45 | D45 | E45 | F45 | G45 | H45 | I45 | ||||||||
| A46 | B46 | C46 | D46 | E46 | F46 | G46 | H46 | I46 | ||||||||
| A47 | B47 | C47 | D47 | E47 | F47 | G47 | H47 | I47 | ||||||||
| A48 | B48 | C48 | D48 | E48 | F48 | G48 | H48 | I48 | ||||||||
| A49 | B49 | C49 | D49 | E49 | F49 | G49 | H49 | I49 | ||||||||
| A50 | B50 | C50 | D50 | E50 | F50 | G50 | H50 | I50 | ||||||||
| A51 | B51 | C51 | D51 | E51 | F51 | G51 | H51 | I51 | ||||||||
| A52 | B52 | C52 | D52 | E52 | F52 | G52 | H52 | I52 | ||||||||
| A53 | B53 | C53 | D53 | E53 | F53 | G53 | H53 | I53 | ||||||||
| A54 | B54 | C54 | D54 | E54 | F54 | G54 | H54 | I54 | ||||||||
| A55 | B55 | C55 | D55 | E55 | F55 | G55 | H55 | I55 | ||||||||
| A56 | B56 | C56 | D56 | E56 | F56 | G56 | H56 | I56 | ||||||||
| A57 | B57 | C57 | D57 | E57 | F57 | G57 | H57 | I57 | ||||||||
| A58 | B58 | C58 | D58 | E58 | F58 | G58 | H58 | I58 | ||||||||
| A59 | B59 | C59 | D59 | E59 | F59 | G59 | H59 | I59 | ||||||||
| A60 | B60 | C60 | D60 | E60 | F60 | G60 | H60 | I60 | ||||||||
| A61 | B61 | C61 | D61 | E61 | F61 | G61 | H61 | I61 | ||||||||
| A62 | B62 | C62 | D62 | E62 | F62 | G62 | H62 | I62 | ||||||||
| A63 | B63 | C63 | D63 | E63 | F63 | G63 | H63 | I63 | ||||||||
| A64 | B64 | C64 | D64 | E64 | F64 | G64 | H64 | I64 | ||||||||
| A65 | B65 | C65 | D65 | E65 | F65 | G65 | H65 | I65 | ||||||||
| A66 | B66 | C66 | D66 | E66 | F66 | G66 | H66 | I66 |
Base Data
| ACT202 ASSIGNMENT DATA - SEMESTER 1 2018 | ||||||
| Student Number | 252967 | |||||
| Student Name | MR MD ASHRAFUL HAQUE (WFD) | |||||
| Sales | Actual Sales Volume 3-months to June | |||||
| April | May | June | July | |||
| Units | 34,500 | 27,600 | 31,050 | 41,400 | 103,400 | |
| Unit selling price | $3,630 | |||||
| The desired finished goods ending inventory for each month is | 20% | of the next month's sales. | ||||
| The full absorption cost of the opening finished goods inventory is | $2,420 | per unit | ||||
| The variable manufacturing cost of the opening finished goods inventory is | $990 | per unit | ||||
| Finished goods inventory on April 1 is | 22,100 | units. | ||||
| Materials be on hand at the beginning of the month to produce | 60% | of that month's estimated sales. | ||||
| Direct Materials used per unit | Actual Materials Used - 3 Months to June | |||||
| Cups | Vanes | Cups | Vanes | |||
| Quantity | 2 | 3 | 157,700 | 34,900 | ||
| Actual Cost of Materials Used - 3 Months to June | ||||||
| Cost per unit | $41 | $55 | $7,758,840 | $4,332,020 | ||
| Actual Labour Used - 3 Months to June | ||||||
| Budgeted Direct Labour time per unit | 4 | (hrs.) | 272,320 | |||
| Actual Cost of Labour Used - 3 Months to June | ||||||
| Direct labour cost per hour | $20 | $6,263,400 | ||||
| Budgeted Manufacturing Overheads | Recent Statistical Data for Mainentance Costs | |||||
| Fixed Cost Component per month | Variable Cost Component per DL Hour | Labour Hrs | Total Maintenance Cost | |||
| Indirect Labour | $28.98 | 665,900 | $40,848,000 | |||
| Power | $2.76 | 759,000 | $44,367,000 | |||
| Maintenance | ??? | ??? | [To be calculated by student] | 696,900 | $42,021,000 | |
| 634,800 | $39,675,000 | |||||
| Supervision | $19,320,000 | |||||
| Depreciation | $1,725,000 | |||||
| Rates and Utilities | $1,425,500 | |||||
| Other | $6,900,000 | $20.70 | ||||
| April | May | June | ||||
| Variable Selling Expenses | $18,785,250 | $15,028,200 | $16,906,725 | |||
| Fixed selling & admin expenses | $12,420,000 | $9,936,000 | $11,178,000 | |||
| Total selling & administrative expenses | $31,205,250 | $24,964,200 | $28,084,725 | |||
| Cash on hand at opening | $1,725,000 | |||||
| Annual Interest Rate on Borrowings | 8% | pa | ||||
| Cash from Sales | ||||||
| Received in Month of Sale | 40% | |||||
| Received in Month After Sale | 58% | |||||
| Balance of Accounts Receivable at the start of the period | $79,900,000 | |||||
| Dividends Paid in May | $610,650 | |||||
| Land purchased in June | $17,940,000 | |||||
Case Details01
| Heidegger Pty Ltd | |
| Heidegger Pty Ltd Case Background | |
| Heidegger Pty Ltd produces anemometers used in the production of wind-powered electricity generating equipment. | |
| The anemometers are sold to various engineering companies that produce wind-powered generators in Australia and Europe. | |
| Projected sales in units for the coming four months are provided in the assignment data sheet. | |
| The following data pertain to production policies and manufacturing specifications followed by Heidegger Pty Ltd._x000D_ The following details are provided in the assignment data sheet: | |
| · Finished goods inventory on April 1. · The full absorption cost of the opening finished goods inventory. · The variable manufacturing cost of the opening finished goods inventory. · The desired finished goods ending inventory for each month. | |
| · The data on materials used. · The amount of materials to be on hand at the beginning of the month · This stipulated amount of materials to be on hand at the beginning of the month is exactly the amount of material on hand on April 1. · (Assume that the material costs per unit are the same throughout the current quarter's production.) | |
| · The direct labour used per unit of output. · The average direct labour cost per hour. | |
| Details of the Overheads for each month are provided in the data list. The Overheads are estimated using a flexible budget formula. (Activity is measured in direct labour hours). You will have to determine the Maintenance cost and relevant statistical data necessary for you to do so is provided in the data List | |
| Monthly selling and administrative overhead expenses are also estimated using a flexible budgeting formula. (Activity is measured in units sold.) Finance charges and bad debts are included in the figures provided and do not need to be identified separately in the selling and administrative overhead expenses. Details are provided in the data list. | |
| Other information provided the assignment data list are: · The unit selling price of the anemometers. · The cost of land to be purchased in May. The company plans to purchase the land for future expansion. · The value and timing of dividends paid to shareholders. · Sales are on credit and the cash receipts pattern for each month is provided, as is the level of Accounts Receivable as at April 1. · Amounts not received in the month following the sale are written off as Bad Debts immediately. · The payment for labour and purchases of materials and other costs are for cash and paid for in the month of acquisition. · There is no Accounts Payable amount for this assignment. · The cash balance on April 1. | |
| If the firm develops a cash shortage by the end of the month, sufficient cash is borrowed to cover the shortage (including any interest payments due). Any cash borrowed is repaid one month later, as is the interest due. The annual interest rate is provided with the assignment data. | |
| During the process of preparing the organisation's budget, the sales manager is discussing the possible outcome of the forthcoming election with the production manager. She noted that if one of the major political parties wins the election and forms government, there is a strong possibility that alternative energy sources such as wind-powered electricity may no longer be as actively supported by the new government as is the case under the current government. | |
| The sales manager's primary concern is that the current market for alternative power generation equipment is already volatile and subject to significant uncertainty. The production manager is also concerned about his plans to build the new highly automated manufacturing facility on the land to be purchased in May. This new manufacturing facility will enable him to manufacture, in-house, the major two parts he is now purchasing for assembly and to significantly automate the assembly process that is currently somewhat labour intensive. | |
| His projections for the new facility indicate a reduction in direct material and direct labour costs of 33% but that his fixed manufacturing overheads are likely to increase by 65% due to the increased investment in production capacity. |
Case Details02
| Heidegger Pty Ltd | |
| Heidegger Pty Ltd Case Background | |
| Heidegger Pty Ltd produces anemometers used in the production of wind-powered electricity generating equipment. | |
| The anemometers are sold to various engineering companies that produce wind-powered generators in Australia and Europe. | |
| Projected sales in units for the coming four months are provided in the assignment data sheet. | |
| The following data pertain to production policies and manufacturing specifications followed by Heidegger Pty Ltd._x000D_ The following details are provided in the assignment data sheet: | |
| · Finished goods inventory on April 1. · The full absorption cost of the opening finished goods inventory. · The variable manufacturing cost of the opening finished goods inventory. · The desired finished goods ending inventory for each month. | |
| · The data on materials used. · The amount of materials to be on hand at the beginning of the month · This stipulated amount of materials to be on hand at the beginning of the month is exactly the amount of material on hand on April 1. · (Assume that the material costs per unit are the same throughout the current quarter's production.) | |
| · The direct labour used per unit of output. · The average direct labour cost per hour. | |
| Details of the Overheads for each month are provided in the data list. The Overheads are estimated using a flexible budget formula. (Activity is measured in direct labour hours). You will have to determine the Maintenance cost and relevant statistical data necessary for you to do so is provided in the data List | |
| Monthly selling and administrative overhead expenses are also estimated using a flexible budgeting formula. (Activity is measured in units sold.) Finance charges and bad debts are included in the figures provided and do not need to be identified separately in the selling and administrative overhead expenses. Details are provided in the data list. | |
| Other information provided the assignment data list are: · The unit selling price of the anemometers. · The cost of land to be purchased in May. The company plans to purchase the land for future expansion. · The value and timing of dividends paid to shareholders. · Sales are on credit and the cash receipts pattern for each month is provided, as is the level of Accounts Receivable as at April 1. · Amounts not received in the month following the sale are written off as Bad Debts immediately. · The payment for labour and purchases of materials and other costs are for cash and paid for in the month of acquisition. · There is no Accounts Payable amount for this assignment. · The cash balance on April 1. | |
| If the firm develops a cash shortage by the end of the month, sufficient cash is borrowed to cover the shortage (including any interest payments due). Any cash borrowed is repaid one month later, as is the interest due. The annual interest rate is provided with the assignment data. | |
| During the process of preparing the organisation's budget, the sales manager is discussing the possible outcome of the forthcoming election with the production manager. She noted that if one of the major political parties wins the election and forms government, there is a strong possibility that alternative energy sources such as wind-powered electricity may no longer be as actively supported by the new government as is the case under the current government. | |
| The sales manager's primary concern is that the current market for alternative power generation equipment is already volatile and subject to significant uncertainty. The production manager is also concerned about his plans to build the new highly automated manufacturing facility on the land to be purchased in May. This new manufacturing facility will enable him to manufacture, in-house, the major two parts he is now purchasing for assembly and to significantly automate the assembly process that is currently somewhat labour intensive. | |
| His projections for the new facility indicate a reduction in direct material and direct labour costs of 33% but that his fixed manufacturing overheads are likely to increase by 65% due to the increased investment in production capacity. |
Case Details03
| Heidegger Pty Ltd | |
| Heidegger Pty Ltd Case Background | |
| Heidegger Pty Ltd produces anemometers used in the production of wind-powered electricity generating equipment. | |
| The anemometers are sold to various engineering companies that produce wind-powered generators in Australia and Europe. | |
| Projected sales in units for the coming four months are provided in the assignment data sheet. | |
| The following data pertain to production policies and manufacturing specifications followed by Heidegger Pty Ltd._x000D_ The following details are provided in the assignment data sheet: | |
| · Finished goods inventory on April 1. · The full absorption cost of the opening finished goods inventory. · The variable manufacturing cost of the opening finished goods inventory. · The desired finished goods ending inventory for each month. | |
| · The data on materials used. · The amount of materials to be on hand at the beginning of the month · This stipulated amount of materials to be on hand at the beginning of the month is exactly the amount of material on hand on April 1. · (Assume that the material costs per unit are the same throughout the current quarter's production.) | |
| · The direct labour used per unit of output. · The average direct labour cost per hour. | |
| Details of the Overheads for each month are provided in the data list. The Overheads are estimated using a flexible budget formula. (Activity is measured in direct labour hours). You will have to determine the Maintenance cost and relevant statistical data necessary for you to do so is provided in the data List | |
| Monthly selling and administrative overhead expenses are also estimated using a flexible budgeting formula. (Activity is measured in units sold.) Finance charges and bad debts are included in the figures provided and do not need to be identified separately in the selling and administrative overhead expenses. Details are provided in the data list. | |
| Other information provided the assignment data list are: · The unit selling price of the anemometers. · The cost of land to be purchased in May. The company plans to purchase the land for future expansion. · The value and timing of dividends paid to shareholders. · Sales are on credit and the cash receipts pattern for each month is provided, as is the level of Accounts Receivable as at April 1. · Amounts not received in the month following the sale are written off as Bad Debts immediately. · The payment for labour and purchases of materials and other costs are for cash and paid for in the month of acquisition. · There is no Accounts Payable amount for this assignment. · The cash balance on April 1. | |
| If the firm develops a cash shortage by the end of the month, sufficient cash is borrowed to cover the shortage (including any interest payments due). Any cash borrowed is repaid one month later, as is the interest due. The annual interest rate is provided with the assignment data. | |
| During the process of preparing the organisation's budget, the sales manager is discussing the possible outcome of the forthcoming election with the production manager. She noted that if one of the major political parties wins the election and forms government, there is a strong possibility that alternative energy sources such as wind-powered electricity may no longer be as actively supported by the new government as is the case under the current government. | |
| The sales manager's primary concern is that the current market for alternative power generation equipment is already volatile and subject to significant uncertainty. The production manager is also concerned about his plans to build the new highly automated manufacturing facility on the land to be purchased in May. This new manufacturing facility will enable him to manufacture, in-house, the major two parts he is now purchasing for assembly and to significantly automate the assembly process that is currently somewhat labour intensive. | |
| His projections for the new facility indicate a reduction in direct material and direct labour costs of 33% but that his fixed manufacturing overheads are likely to increase by 65% due to the increased investment in production capacity. |
Case Details04
| Heidegger Pty Ltd | |
| Heidegger Pty Ltd Case Background | |
| Heidegger Pty Ltd produces anemometers used in the production of wind-powered electricity generating equipment. | |
| The anemometers are sold to various engineering companies that produce wind-powered generators in Australia and Europe. | |
| Projected sales in units for the coming four months are provided in the assignment data sheet. | |
| The following data pertain to production policies and manufacturing specifications followed by Heidegger Pty Ltd._x000D_ The following details are provided in the assignment data sheet: | |
| · Finished goods inventory on April 1. · The full absorption cost of the opening finished goods inventory. · The variable manufacturing cost of the opening finished goods inventory. · The desired finished goods ending inventory for each month. | |
| · The data on materials used. · The amount of materials to be on hand at the beginning of the month · This stipulated amount of materials to be on hand at the beginning of the month is exactly the amount of material on hand on April 1. · (Assume that the material costs per unit are the same throughout the current quarter's production.) | |
| · The direct labour used per unit of output. · The average direct labour cost per hour. | |
| Details of the Overheads for each month are provided in the data list. The Overheads are estimated using a flexible budget formula. (Activity is measured in direct labour hours). You will have to determine the Maintenance cost and relevant statistical data necessary for you to do so is provided in the data List | |
| Monthly selling and administrative overhead expenses are also estimated using a flexible budgeting formula. (Activity is measured in units sold.) Finance charges and bad debts are included in the figures provided and do not need to be identified separately in the selling and administrative overhead expenses. Details are provided in the data list. | |
| Other information provided the assignment data list are: · The unit selling price of the anemometers. · The cost of land to be purchased in May. The company plans to purchase the land for future expansion. · The value and timing of dividends paid to shareholders. · Sales are on credit and the cash receipts pattern for each month is provided, as is the level of Accounts Receivable as at April 1. · Amounts not received in the month following the sale are written off as Bad Debts immediately. · The payment for labour and purchases of materials and other costs are for cash and paid for in the month of acquisition. · There is no Accounts Payable amount for this assignment. · The cash balance on April 1. | |
| If the firm develops a cash shortage by the end of the month, sufficient cash is borrowed to cover the shortage (including any interest payments due). Any cash borrowed is repaid one month later, as is the interest due. The annual interest rate is provided with the assignment data. | |
| During the process of preparing the organisation's budget, the sales manager is discussing the possible outcome of the forthcoming election with the production manager. She noted that if one of the major political parties wins the election and forms government, there is a strong possibility that alternative energy sources such as wind-powered electricity may no longer be as actively supported by the new government as is the case under the current government. | |
| The sales manager's primary concern is that the current market for alternative power generation equipment is already volatile and subject to significant uncertainty. The production manager is also concerned about his plans to build the new highly automated manufacturing facility on the land to be purchased in May. This new manufacturing facility will enable him to manufacture, in-house, the major two parts he is now purchasing for assembly and to significantly automate the assembly process that is currently somewhat labour intensive. | |
| His projections for the new facility indicate a reduction in direct material and direct labour costs of 33% but that his fixed manufacturing overheads are likely to increase by 65% due to the increased investment in production capacity. |
Case Details05
| Heidegger Pty Ltd | |
| Heidegger Pty Ltd Case Background | |
| Heidegger Pty Ltd produces anemometers used in the production of wind-powered electricity generating equipment. | |
| The anemometers are sold to various engineering companies that produce wind-powered generators in Australia and Europe. | |
| Projected sales in units for the coming four months are provided in the assignment data sheet. | |
| The following data pertain to production policies and manufacturing specifications followed by Heidegger Pty Ltd._x000D_ The following details are provided in the assignment data sheet: | |
| · Finished goods inventory on April 1. · The full absorption cost of the opening finished goods inventory. · The variable manufacturing cost of the opening finished goods inventory. · The desired finished goods ending inventory for each month. | |
| · The data on materials used. · The amount of materials to be on hand at the beginning of the month · This stipulated amount of materials to be on hand at the beginning of the month is exactly the amount of material on hand on April 1. · (Assume that the material costs per unit are the same throughout the current quarter's production.) | |
| · The direct labour used per unit of output. · The average direct labour cost per hour. | |
| Details of the Overheads for each month are provided in the data list. The Overheads are estimated using a flexible budget formula. (Activity is measured in direct labour hours). You will have to determine the Maintenance cost and relevant statistical data necessary for you to do so is provided in the data List | |
| Monthly selling and administrative overhead expenses are also estimated using a flexible budgeting formula. (Activity is measured in units sold.) Finance charges and bad debts are included in the figures provided and do not need to be identified separately in the selling and administrative overhead expenses. Details are provided in the data list. | |
| Other information provided the assignment data list are: · The unit selling price of the anemometers. · The cost of land to be purchased in May. The company plans to purchase the land for future expansion. · The value and timing of dividends paid to shareholders. · Sales are on credit and the cash receipts pattern for each month is provided, as is the level of Accounts Receivable as at April 1. · Amounts not received in the month following the sale are written off as Bad Debts immediately. · The payment for labour and purchases of materials and other costs are for cash and paid for in the month of acquisition. · There is no Accounts Payable amount for this assignment. · The cash balance on April 1. | |
| If the firm develops a cash shortage by the end of the month, sufficient cash is borrowed to cover the shortage (including any interest payments due). Any cash borrowed is repaid one month later, as is the interest due. The annual interest rate is provided with the assignment data. | |
| During the process of preparing the organisation's budget, the sales manager is discussing the possible outcome of the forthcoming election with the production manager. She noted that if one of the major political parties wins the election and forms government, there is a strong possibility that alternative energy sources such as wind-powered electricity may no longer be as actively supported by the new government as is the case under the current government. | |
| The sales manager's primary concern is that the current market for alternative power generation equipment is already volatile and subject to significant uncertainty. The production manager is also concerned about his plans to build the new highly automated manufacturing facility on the land to be purchased in May. This new manufacturing facility will enable him to manufacture, in-house, the major two parts he is now purchasing for assembly and to significantly automate the assembly process that is currently somewhat labour intensive. | |
| His projections for the new facility indicate a reduction in direct material and direct labour costs of 33% but that his fixed manufacturing overheads are likely to increase by 65% due to the increased investment in production capacity. |
Case Details06
| Heidegger Pty Ltd | |
| Heidegger Pty Ltd Case Background | |
| Heidegger Pty Ltd produces anemometers used in the production of wind-powered electricity generating equipment. | |
| The anemometers are sold to various engineering companies that produce wind-powered generators in Australia and Europe. | |
| Projected sales in units for the coming four months are provided in the assignment data sheet. | |
| The following data pertain to production policies and manufacturing specifications followed by Heidegger Pty Ltd._x000D_ The following details are provided in the assignment data sheet: | |
| · Finished goods inventory on April 1. · The full absorption cost of the opening finished goods inventory. · The variable manufacturing cost of the opening finished goods inventory. · The desired finished goods ending inventory for each month. | |
| · The data on materials used. · The amount of materials to be on hand at the beginning of the month · This stipulated amount of materials to be on hand at the beginning of the month is exactly the amount of material on hand on April 1. · (Assume that the material costs per unit are the same throughout the current quarter's production.) | |
| · The direct labour used per unit of output. · The average direct labour cost per hour. | |
| Details of the Overheads for each month are provided in the data list. The Overheads are estimated using a flexible budget formula. (Activity is measured in direct labour hours). You will have to determine the Maintenance cost and relevant statistical data necessary for you to do so is provided in the data List | |
| Monthly selling and administrative overhead expenses are also estimated using a flexible budgeting formula. (Activity is measured in units sold.) Finance charges and bad debts are included in the figures provided and do not need to be identified separately in the selling and administrative overhead expenses. Details are provided in the data list. | |
| Other information provided the assignment data list are: · The unit selling price of the anemometers. · The cost of land to be purchased in May. The company plans to purchase the land for future expansion. · The value and timing of dividends paid to shareholders. · Sales are on credit and the cash receipts pattern for each month is provided, as is the level of Accounts Receivable as at April 1. · Amounts not received in the month following the sale are written off as Bad Debts immediately. · The payment for labour and purchases of materials and other costs are for cash and paid for in the month of acquisition. · There is no Accounts Payable amount for this assignment. · The cash balance on April 1. | |
| If the firm develops a cash shortage by the end of the month, sufficient cash is borrowed to cover the shortage (including any interest payments due). Any cash borrowed is repaid one month later, as is the interest due. The annual interest rate is provided with the assignment data. | |
| During the process of preparing the organisation's budget, the sales manager is discussing the possible outcome of the forthcoming election with the production manager. She noted that if one of the major political parties wins the election and forms government, there is a strong possibility that alternative energy sources such as wind-powered electricity may no longer be as actively supported by the new government as is the case under the current government. | |
| The sales manager's primary concern is that the current market for alternative power generation equipment is already volatile and subject to significant uncertainty. The production manager is also concerned about his plans to build the new highly automated manufacturing facility on the land to be purchased in May. This new manufacturing facility will enable him to manufacture, in-house, the major two parts he is now purchasing for assembly and to significantly automate the assembly process that is currently somewhat labour intensive. | |
| His projections for the new facility indicate a reduction in direct material and direct labour costs of 33% but that his fixed manufacturing overheads are likely to increase by 65% due to the increased investment in production capacity. |